system

Abstract

It enables two-way communication with animals. [Solution] The system includes means for acquiring animal sound data and means for transmitting the sound data to a server. The system includes means for analyzing the audio data on a server to identify the animal's emotions or intentions, means for translating the identified emotions or intentions into human language and transmitting them to a terminal, and means for converting the human language into audio that the animal can understand and outputting it to the animal.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The difficulty of communicating with animals has become a major issue, especially for households with pets and animal protection activities. Since it is impossible to accurately understand the behaviors and voices shown by animals, in many cases, there is a possibility of misinterpreting the health status and psychological needs of animals. Furthermore, in order to promote the coexistence of wild animals and humans, technologies for accurately grasping the thoughts and intentions of animals are required.

Means for Solving the Problems

[0005] This invention provides a means for acquiring animal voice data and analyzing that voice data on a server. This makes it possible to identify the animal's emotions or intentions, translate them into human language, and transmit them to a terminal. Furthermore, by providing a system that includes means for converting a message input by a human to an animal into voice that the animal can understand and outputting it to the animal, this invention enables two-way communication with animals.

[0006] "Animal sound data" refers to data obtained by converting the sounds and noises made by animals into a digital format.

[0007] A "server" is a computer system that receives audio data over a network and is responsible for processing and analyzing that data.

[0008] "Identifying emotions or intentions" means recognizing the emotional state or purpose behind the sounds or behaviors exhibited by an animal.

[0009] "Translating into human language" means converting animal emotions and intentions into natural language and expressing them in a form that humans can understand.

[0010] A "terminal" is a device operated by the user that communicates with a server to send and receive audio data and display translation results.

[0011] "Converting input words into animal-readable speech" means analyzing human speech entered by the user and converting it into a speech format that animals can understand. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3]It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the language used in the following description will be explained.

[0015] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention is a system for facilitating communication between humans and animals by utilizing animal sounds. This system operates with a server and terminals working together to analyze animal sound data, convey its content to humans, and also transmit messages from humans to animals in an understandable format.

[0034] First, the device records the animal's voice. For example, a user might use their smartphone to capture the sound of their pet dog barking. This recorded audio data is then sent to a server via the internet.

[0035] Next, the server analyzes the received audio data using an AI engine. Here, the server identifies what emotions or intentions the animal is currently experiencing based on the animal's unique vocal characteristics. This process allows the server to estimate states such as "wanting to play" or "feeling anxious."

[0036] Based on the analysis results, the server translates the animal's emotions and intentions into natural language. This process allows users to understand the animal's state in a format they can easily comprehend. The translated results are sent to the terminal and displayed to the user.

[0037] When a user enters a message they want to convey to an animal, the device sends that message to a server. The server converts human language into speech that animals can understand. This speech is then played back on the device and conveyed to the animal.

[0038] The system described above can be used in a specific scenario, such as when a user spends a holiday at home with their dog. When the dog makes a sound indicating it wants to play, the user can quickly understand this and respond at the appropriate time.

[0039] Thus, the system of the present invention can be used to facilitate effective communication with animals in a variety of situations. For animal lovers and pet owners, it is a valuable tool that allows them to gain a deeper understanding of the animal's psychological state and reflect that understanding in their behavior.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user activates the device's recording function and prepares to record animal sounds. The recording process begins when the user presses the "Start Recording" button.

[0043] Step 2:

[0044] The device saves the recorded animal audio data as a temporary file. In this process, the audio is captured as digital data and converted to a format that can be transmitted later.

[0045] Step 3:

[0046] The device transmits stored animal audio data to the server via an internet connection. A secure protocol is used for data transmission to ensure that the audio is delivered accurately and safely to the server.

[0047] Step 4:

[0048] The server analyzes the received audio data. The server's AI engine works to analyze the audio patterns in order to determine the emotions and intentions from the animal's voice.

[0049] Step 5:

[0050] The server translates the animal's emotions or intentions into human language based on the analysis results. This translation is then converted into easy-to-understand text and formatted in a way that is easy for the user to comprehend.

[0051] Step 6:

[0052] The server sends the translated text back to the terminal. The terminal prepares to display this information on the screen for the user to see.

[0053] Step 7:

[0054] The user checks the translation displayed on the device and enters a response. For example, they might enter the message, "Are you hungry?"

[0055] Step 8:

[0056] The terminal sends the message entered by the user to the server. At this point, the message needs to be translated so that the animal can understand it, and is therefore processed by the server.

[0057] Step 9:

[0058] The server converts the received user message into an audio format that animals can understand. The translated audio data is then sent to the device.

[0059] Step 10:

[0060] The device plays animal sounds received from the server. It is expected that by hearing these sounds, the animals will recognize the user's intentions and take appropriate action.

[0061] (Example 1)

[0062] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] Communication between animals and humans is often fraught with difficulties in understanding emotions and intentions. This makes it challenging to assess an animal's condition and take appropriate action. Furthermore, it is difficult for humans to interpret animal vocalizations as meaningful information and to effectively communicate their own messages to animals.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] In this invention, the server includes means for analyzing animal vocal information to identify emotions and intentions, means for translating the identified information into language, and means for converting it into animal-understandable speech and outputting it. This makes it possible to accurately understand the emotions and intentions of animals and to effectively convey messages from humans to animals.

[0066] "Auditory information" refers to information that is recorded from sounds emitted by animals or humans and treated as digital data.

[0067] An "information processing device" is a server or computer system that analyzes audio information and performs specific processing.

[0068] A "terminal device" is a device that a user directly operates to display information or play audio.

[0069] "Natural language processing" refers to a technology for translating audio information into language, and it is a function that uses artificial intelligence to analyze meaning and intent.

[0070] "Animal-ready audio" refers to audio data generated in a format that animals can understand.

[0071] This invention is a system for effective communication between humans and animals using animal sounds. The user's terminal is equipped with hardware for recording sound, such as a microphone. The user can use the sound recording function to collect sounds emitted by animals, such as pets. This information is transmitted from the terminal to an information processing device (server) via the internet.

[0072] The server receives audio information and analyzes it using a generative AI model. Specifically, it uses natural language processing capabilities to identify the animal's emotions and intentions from the audio data. This involves technologies such as deep learning algorithms. During this process, characteristic audio patterns specific to each animal species are analyzed.

[0073] The identified emotions and intentions are translated into a language easily understood by the user and sent to the terminal device. The user can check the translation results on the terminal's display. Furthermore, when the user enters a message they want to convey to an animal into the terminal, the message is analyzed by a server and converted into animal-readable speech. The terminal then plays the converted speech to convey the user's intentions to the animal.

[0074] A concrete example is when a user enters a prompt such as, "Analyze the dog's bark and translate it into a phrase that expresses its emotion." This prompt allows the server to analyze the dog's bark, identify its intention (e.g., "I want to play"), and inform the user. This enables animal lovers and pet owners to better understand their animals' emotions and facilitate smoother communication in daily life.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The user captures animal sounds using the device's recording function. In this step, the user uses the device's built-in microphone to record the barking of an animal, such as a pet dog. The recorded audio data is obtained as input.

[0078] Step 2:

[0079] The device sends the recorded audio data to the server over the internet. During this transmission, the audio data is compressed or encoded as a digital file and sent using a secure communication protocol (e.g., SSL / TLS). The server then receives the audio data as input.

[0080] Step 3:

[0081] The server analyzes the received audio data. In this analysis process, the audio data is first input into a deep learning model to identify the animal's emotions and intentions. This process uses a generative AI model to extract audio features and estimate emotions and intentions based on them. As a result of the analysis, an intention such as "I want to play" is output.

[0082] Step 4:

[0083] The server translates the analysis results into a language that the user can easily understand. This translation step converts identified emotions and intentions into natural language text. A generative AI model is used for translation, and the result is output as a text message.

[0084] Step 5:

[0085] The server sends the translated result to the terminal. The terminal displays this result on its screen to inform the user. The user can then check the message displayed on the terminal and understand the animal's condition.

[0086] Step 6:

[0087] The user enters a message they want to convey to the animal into the device. In this step, the user uses the text input function to enter a message such as "Please wait a moment." This message is then received as input.

[0088] Step 7:

[0089] The terminal sends the entered message to the server. The server receives this message and converts it into animal sounds using a generation AI model. The resulting audio file is then output.

[0090] Step 8:

[0091] The device plays animal sounds transmitted from the server. During playback, the converted sounds are output from the device's speaker, allowing the user's intentions to be conveyed to the animal.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] In recent years, there has been a growing need to accurately understand the emotions and intentions of animals in communication between pets and their owners. However, there is a lack of technology to accurately analyze animal sounds and convey them in a way that is easily understood by humans. Furthermore, there is the challenge of conveying human messages in a way that animals can understand. In addition, there is a lack of systems in place at physical stores such as pet shops to support owners' purchasing decisions based on an understanding of the animals' condition.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] In this invention, the server includes means for analyzing animal vocal information and identifying the animal's emotions or intentions; means for translating the identified emotions or intentions into natural language and transmitting them to an information terminal; and means for converting the natural language into a form that the animal can understand and outputting it to the animal. This facilitates smooth communication between animals and their owners, improves the customer experience in physical stores, and enables effective product recommendations.

[0097] "Animal vocal information" refers to digitized data of sounds emitted by animals. This data serves as a basis for analyzing animals' emotions and intentions.

[0098] A "central processing unit" refers to a computer system that receives, analyzes, and translates audio information. This device interacts with terminals via a network.

[0099] "Natural language" refers to the language that humans use on a daily basis, and is used to communicate the emotions and intentions of animals in a way that is easily understood by humans.

[0100] An "information terminal" refers to a device used by a user to receive and display information. Specifically, this includes smartphones and tablets.

[0101] "Animal products" refer to products tailored to the characteristics and needs of animals. Specifically, this includes toys, food, and care products, and the role is to support the recommendation of such products.

[0102] A "generative AI model" refers to an artificial intelligence framework that learns from data and performs tasks such as analyzing animal voices and generating natural language. It is used to support smooth communication between animals and humans.

[0103] To realize this invention, the server and terminal play a central role in the system. The server receives animal vocal information and analyzes it using a generative AI model. This analysis process uses an algorithm that identifies emotions and intentions from the animal's vocal characteristics. Specifically, it estimates the animal's state, such as "wanting to play" or "feeling anxious," based on the frequency components and rhythmic patterns of the vocals.

[0104] Once the analysis is complete, the server translates these estimation results into natural language. The translated results are then sent directly to the terminal. The terminal is the user's smartphone or tablet, which has the capability to display these translated results on its screen. The displayed information helps the user quickly understand their pet's condition and take appropriate action.

[0105] On the other hand, when a user enters a message into the device, the device sends that message back to the server. The server synthesizes the entered human language into speech that animals can understand. This synthesis technology typically includes the functions of a speech synthesis engine. The synthesized speech is played back from the device to the animal, enabling smooth communication.

[0106] As a concrete example, in pet shops, this system would be used to enable customers to understand their pet's feelings in real time and instantly purchase the necessary products. In this case, an example of a prompt text would be, "Analyze the dog's voice, estimate its emotions, and display the result in Japanese."

[0107] This system is expected to improve the quality of communication between pets and their owners, and further enhance customer service at pet shops.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The device records animal sounds using its microphone and saves them as digital audio data. The user launches the device's recording application and captures their pet's sounds using the record button. This recorded data is sent to the server as initial input data.

[0111] Step 2:

[0112] The server analyzes the received audio data. Using a generative AI model, it analyzes the frequency components and temporal features of the audio to estimate the animal's emotions and intentions. The estimation results are output as specific emotional states such as "want to play" or "anxious" through data calculations.

[0113] Step 3:

[0114] The server translates the analyzed emotions and intentions into natural language. Using a generative AI model, the estimated emotions are converted into standard Japanese, generating a message that is easy for the user to understand. This content is then formatted as data to be sent to the device.

[0115] Step 4:

[0116] The device receives the translation results sent from the server and displays them on the screen. Through the device screen, the user can understand their pet's emotional state. For example, a message such as "Your pet wants to play" might be displayed.

[0117] Step 5:

[0118] The user enters the message they want to convey to their pet using the input interface built into the device. This input is then sent back to the server as data and processed into a communication format for the animal.

[0119] Step 6:

[0120] The server converts user input messages into speech that animals can understand. Using a generative AI model, it synthesizes the input Japanese into animal-friendly speech with specific frequencies and intonations. This result is then constructed as output data.

[0121] Step 7:

[0122] The device plays the converted audio data received from the server and emits the voice to the animal. This conveys the user's intentions to the pet. This process is completed when the animal actually changes its behavior in response to the message.

[0123] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0124] This invention provides a system that combines an emotion engine that analyzes animal sounds and recognizes user emotions. This system aims to improve communication between animals and humans through the cooperation of a server and a terminal. Furthermore, by using the emotion engine, it achieves more appropriate interaction while considering the user's emotional state.

[0125] First, the device records the voices of both the user and the animal. During this process, the user's voice is analyzed by an emotion engine to identify the user's emotions, while the animal's voice is sent to the server.

[0126] After receiving animal voice data, the server uses an AI engine to analyze the data. This analysis identifies the animal's emotions and intentions, and then the process of translating this into human language begins.

[0127] Next, the emotion engine processes the user's emotional data and suggests the optimal communication content to convey to the animal. Specifically, if the user is feeling stressed, the content of the interaction with the animal can be adjusted to promote mutual relaxation.

[0128] Based on the translated animal's emotions or intentions, and suggestions from the emotion engine, the server sends information to the terminal. The terminal displays this information to the user. Based on this information, the user can decide how to respond to the animal.

[0129] Furthermore, when a user enters their own words, those words are sent back to the server and converted into an appropriate voice format for the animal. This ensures that the message is delivered to the animal and communication is completed.

[0130] As a concrete example, consider a scenario where a user is relaxing with their pet cat. If the cat makes a sound indicating it wants attention, the system will display the most appropriate interaction method based on the user's current emotional state.

[0131] This system allows users to interact with animals while harmonizing their own emotions with the animals' states, thereby improving their quality of life.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The device simultaneously records audio data from both the user and the animal. Recording begins when the user presses the "Start Recording" button, and the device captures the data using its built-in microphone.

[0135] Step 2:

[0136] The device splits the recorded data into user voice data and animal voice data, saving them as temporary files. This operation is necessary to analyze the two voices individually.

[0137] Step 3:

[0138] The emotion engine analyzes the user's voice data to identify the user's emotional state. This process estimates emotions by evaluating factors such as tone, speed, and language patterns within the voice.

[0139] Step 4:

[0140] The device sends animal sound data to the server. A secure communication protocol is used for data transmission, and it is ensured that the data reaches the server accurately.

[0141] Step 5:

[0142] The server uses an AI engine to analyze the animal's voice data it receives. The server detects patterns in the animal's vocalizations and identifies the emotions and intentions they convey.

[0143] Step 6:

[0144] The server translates the analysis results into human language, expressing the animal's emotions and intentions. Simultaneously, it considers the user's emotional state to generate suggestions from the emotion engine.

[0145] Step 7:

[0146] The server sends the translation results and suggestions from the engine to the terminal. The terminal receives the information and promptly notifies the user.

[0147] Step 8:

[0148] The device displays the information it receives to the user. Based on the displayed information, the user can decide on appropriate actions and words for the animal.

[0149] Step 9:

[0150] The user enters a response into the terminal, and the terminal sends that input data to the server. This data is a message that should be understood by animals.

[0151] Step 10:

[0152] The server converts the user's words into an animal-readable voice format and sends this voice to the device. The device then plays this voice and communicates with the animal.

[0153] Thus, this system accurately recognizes the emotions of both the user and the animal, and highly optimizes communication.

[0154] (Example 2)

[0155] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0156] In animal-human communication, there is a need for a system that can accurately understand the animal's emotions and intentions, and enable appropriate human responses based on that understanding. However, conventional systems have the problem of low accuracy in identifying emotions from animal sounds and the inability to suggest communication that takes the user's emotions into consideration. Therefore, there is a need to provide a system that can realize ideal interaction between animals and humans and improve their quality of life.

[0157] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0158] In this invention, the server includes means for analyzing animal vocal information and identifying its emotions and intentions, means for converting the identified emotions and intentions into human language, and means for detecting the user's vocal emotions and suggesting a communication method that corresponds to the user's emotions. This enables a highly accurate understanding of the animal's emotions and intentions, as well as appropriate interaction that takes the user's emotions into consideration.

[0159] "Auditory information" refers to sound data obtained from animals or users, including elements such as pitch, intensity, and temporal changes in sound.

[0160] A "processing device" refers to a computer system that analyzes audio data to identify the emotions and intentions of animals.

[0161] "Emotion or intention" refers to the mental or behavioral state indicated by the sounds an animal makes, as determined by analysis.

[0162] "Human language" refers to the natural forms of language used to translate the intentions and emotions of animals, and which are understandable to humans.

[0163] A "terminal device" refers to a device that serves as an interface with the end user, allowing the user to receive and input voice information.

[0164] "Vocal emotion" refers to the emotional state emanating from the user's voice, including emotional responses such as stress and relaxation.

[0165] "Communication methods" refer to specific behaviors and ways of dialogue proposed to facilitate interaction with animals.

[0166] A "generative AI model" refers to an artificial intelligence model used for analyzing and translating speech data, and is the algorithm that underpins the entire process.

[0167] A "prompt statement" refers to a trigger statement that is input into the generation AI model. Based on this, the model operates and generates results.

[0168] This invention is a system for enhancing communication between animals and humans, where a server, terminal, and user work together seamlessly. The specific configuration for carrying out this invention is shown below.

[0169] First, the device acquires the voices of both the user and the animal. The device is a smartphone or a dedicated device that collects voice data in real time using its built-in microphone. The user's voice data is analyzed by an emotion engine within the device, and the user's emotions are identified, for example, as "peaceful" or "exhilarated." The animal's voice data is formatted and then sent to a server via the internet.

[0170] After receiving audio data, the server analyzes it using an AI engine. Specifically, it uses generative AI models such as TENSORFLOW® and PyTorch to identify emotions and intentions from animal voices. When a state such as "excited" is recognized, it translates it into human language. This translated information is then sent to the terminal.

[0171] The user determines how to interact with the animal based on the information provided by the device. Furthermore, if the user has something they want to communicate to the animal, they can input it into the device. The input is then sent back to the server and converted into an animal-friendly voice format. For example, a message like "Let's play together" would be output in a voice customized for the animal.

[0172] As a concrete example, consider a scenario where a user is spending time with their pet dog. If the dog makes a sound indicating it wants to go outside, the system suggests an interaction method based on the user's current emotional state, such as "taking the dog for a walk with leadership." This system allows users to communicate in a way that harmonizes their own emotions while understanding the animal's state.

[0173] An example of a prompt message might be, "Analyze the sound of a dog barking and translate its emotion." This allows the system to function comprehensively and play a role in improving the quality of life for both animals and humans.

[0174] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0175] Step 1:

[0176] The device acquires user and animal voices in real time. When the user uses the device's microphone to collect voices, the audio data is immediately digitized and pre-processed to analyze the user's emotions. The input is the user's and animal's voices, and the output is digitized audio data. Specific operations include noise reduction and conversion of the audio to the time domain.

[0177] Step 2:

[0178] The device transmits the user's voice data to its built-in emotion engine. The emotion engine uses a generative AI model to analyze the characteristics of the voice and identify the user's emotional state, such as "relaxed" or "stressed." The input is the digitized user's voice, and the output is the identified emotional state. Specifically, the process involves spectrogram conversion and comparison with the emotion model.

[0179] Step 3:

[0180] The terminal transmits animal voice data to the server. For transmission, the voice data is effectively packaged and delivered to the server via a secure communication method. The input is digitized animal voice, and the output is the packaged data sent to the server. Specific operations include data compression and transfer using a secure protocol.

[0181] Step 4:

[0182] The server analyzes the received animal voice data using an AI engine. The generative AI model used here evaluates the animal's voice patterns and identifies its emotions and intentions. The input is the animal voice package received by the server, and the output is the identified emotions and intentions of the animal. Specifically, the process involves filtering the voice waveform and applying an emotion identification algorithm.

[0183] Step 5:

[0184] The server translates the identified animal's emotions or intentions into human language and sends it to the terminal. The translated information is provided in a format that is easy for the user to understand. The input is the identified animal's emotions or intentions, and the output is the translation into human language. Specifically, text generation is performed using a natural language processing module.

[0185] Step 6:

[0186] The user decides how to interact with the animal based on its state and emotions presented by the device. If necessary, the user interactively determines a course of action. The input is translated animal emotion information, and the output is the user's decision to act. The specific actions involve the user's decision-making process based on the provided information.

[0187] Step 7:

[0188] When a user wants to send a message to an animal, they type the words into the device. These words are sent to a server and converted into an animal-readable audio format. The input is text information entered by the user, and the output is played back on the device as audio for the animal. Specifically, text-to-speech technology is used for speech generation.

[0189] (Application Example 2)

[0190] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0191] Smooth communication between animals and humans is crucial for deepening mutual understanding, especially in relationships with pets. However, since animals cannot directly communicate with humans, accurately understanding their emotions and intentions is difficult. Furthermore, teaching animals appropriate communication methods based on human emotional states is an even more complex challenge. There is a need to solve these problems and develop safe and effective means of facilitating interaction between visitors and animals in pet shops and veterinary clinics.

[0192] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0193] In this invention, the server includes means for analyzing animal voice data to identify emotions or intentions, means for analyzing human emotion data to recommend optimal communication, and means for proposing interaction methods suitable for both animals and humans. This enables communication in which animals and humans can mutually understand each other's emotions and intentions.

[0194] "Animal sound data" refers to digital recordings of sounds emitted by animals.

[0195] A "server" is a computing device that receives and analyzes animal and human voice data.

[0196] "Means for identifying emotions or intentions" refers to technologies and algorithms for analyzing and revealing the emotions and behavioral intentions of animals from received audio data.

[0197] "Human emotion data" refers to data used to identify a person's emotional state based on their voice and other biometric information.

[0198] "Means of recommending optimal communication" refers to technologies and systems that propose methods for smooth interaction between humans and animals based on analyzed emotional data.

[0199] A "terminal" is a device that displays information sent from a server to the user and also accepts input from the user.

[0200] "Translation means" are technologies or devices that translate animal emotions or intentions into language that humans can understand, or vice versa.

[0201] "Means of proposing methods of interaction" refer to technologies and functions that present optimal methods of interaction while taking into account the emotions of animals and humans.

[0202] The system for implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user.

[0203] First, the device is equipped with microphones to record animal and user voices. The recorded audio data is sent to a server in digital format. The server uses an advanced analysis engine to identify the emotions and intentions of the animal's voice. The software used includes natural language processing libraries and speech sentiment analysis libraries (e.g., Python's NLTK and OpenAI® models).

[0204] Next, the server uses an emotion recognition engine (e.g., Microsoft® Azure® Emotion API) to analyze the user's voice and recognize their emotions. This emotion data is then analyzed in conjunction with animal emotion data and used in a process to suggest the most appropriate communication method. The recommendations generated by the AI ​​model are presented to the user visually through the device's display.

[0205] Users can view suggested methods via their device and respond to animals using their own actions and voice. The voice input and choices entered by the user are sent back to the server and converted into speech that animals can understand. This conversion uses text-to-speech technology (e.g., Google® Text-to-Speech).

[0206] As a concrete example, let's consider an application in a pet shop. When a customer is interacting with a cat in the store, if the cat makes a sound indicating it wants to play, the system will use the user's emotional state to suggest the best way for the user to interact with the cat. For example, a user who is feeling stressed will be offered suggestions for conversation and play to help them relax with the cat. Examples of prompts in this case could include, "We will analyze the sounds the cat made to understand its emotions," or "We will suggest how the user should interact to help them relax."

[0207] This system offers an innovative means for better communication between animals and humans, and its implementation is particularly useful in places where contact with animals is frequent.

[0208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0209] Step 1:

[0210] The device simultaneously records the voices of both the user and the animal. The input is real-time audio data obtained through the device's microphone. This audio data is converted to a digital format and prepared for transmission to the server.

[0211] Step 2:

[0212] The server receives animal voice data sent from the terminal. The server uses an AI engine to analyze this input data, interpreting the animal's emotions and intentions. Here, a natural language processing library is used to process the data and convert it into human language for translation.

[0213] Step 3:

[0214] The server receives the user's voice data and uses an emotion engine to analyze the user's emotional state. The input voice data is converted into text data through the engine, and the user's emotions are output as numerical and textual information. This output is used for subsequent analysis.

[0215] Step 4:

[0216] The server determines the optimal communication method based on the analyzed animal's emotions and the user's emotions. A generative AI model is used here to create specific dialogue content as prompts. The output is information about the proposed interaction content.

[0217] Step 5:

[0218] The terminal receives information about the interaction content sent from the server and visualizes it for the user. Specific action instructions and communication methods displayed on the terminal are output in a format that the user can easily understand.

[0219] Step 6:

[0220] The user communicates with the animal according to the information presented through the device. The user's input (e.g., selected communication mode) is resent from the device to the server and proceeds to the step where it is converted into voice for the animal.

[0221] Step 7:

[0222] The server converts the user's input into an audio format that animals can understand and outputs it to the animals via the terminal. Here, the text-to-speech conversion process takes place, resulting in output data for directly approaching the animals.

[0223] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0224] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0225] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0226] [Second Embodiment]

[0227] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0228] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0229] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0230] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0231] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0232] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0233] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0234] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0235] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0236] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0237] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0238] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0239] This invention is a system for facilitating communication between humans and animals by utilizing animal sounds. This system operates with a server and terminals working together to analyze animal sound data, convey its content to humans, and also transmit messages from humans to animals in an understandable format.

[0240] First, the device records the animal's voice. For example, a user might use their smartphone to capture the sound of their pet dog barking. This recorded audio data is then sent to a server via the internet.

[0241] Next, the server analyzes the received audio data using an AI engine. Here, the server identifies what emotions or intentions the animal is currently experiencing based on the animal's unique vocal characteristics. This process allows the server to estimate states such as "wanting to play" or "feeling anxious."

[0242] Based on the analysis results, the server translates the animal's emotions and intentions into natural language. This process allows users to understand the animal's state in a format they can easily comprehend. The translated results are sent to the terminal and displayed to the user.

[0243] When a user enters a message they want to convey to an animal, the device sends that message to a server. The server converts human language into speech that animals can understand. This speech is then played back on the device and conveyed to the animal.

[0244] The system described above can be used in a specific scenario, such as when a user spends a holiday at home with their dog. When the dog makes a sound indicating it wants to play, the user can quickly understand this and respond at the appropriate time.

[0245] Thus, the system of the present invention can be used to facilitate effective communication with animals in a variety of situations. For animal lovers and pet owners, it is a valuable tool that allows them to gain a deeper understanding of the animal's psychological state and reflect that understanding in their behavior.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user activates the device's recording function and prepares to record animal sounds. The recording process begins when the user presses the "Start Recording" button.

[0249] Step 2:

[0250] The device saves the recorded animal audio data as a temporary file. In this process, the audio is captured as digital data and converted to a format that can be transmitted later.

[0251] Step 3:

[0252] The device transmits stored animal audio data to the server via an internet connection. A secure protocol is used for data transmission to ensure that the audio is delivered accurately and safely to the server.

[0253] Step 4:

[0254] The server analyzes the received audio data. The server's AI engine works to analyze the audio patterns in order to determine the emotions and intentions from the animal's voice.

[0255] Step 5:

[0256] The server translates the animal's emotions or intentions into human language based on the analysis results. This translation is then converted into easy-to-understand text and formatted in a way that is easy for the user to comprehend.

[0257] Step 6:

[0258] The server sends the translated text back to the terminal. The terminal prepares to display this information on the screen for the user to see.

[0259] Step 7:

[0260] The user checks the translation displayed on the device and enters a response. For example, they might enter the message, "Are you hungry?"

[0261] Step 8:

[0262] The terminal sends the message entered by the user to the server. At this point, the message needs to be translated so that the animal can understand it, and is therefore processed by the server.

[0263] Step 9:

[0264] The server converts the received user message into an audio format that animals can understand. The translated audio data is then sent to the device.

[0265] Step 10:

[0266] The device plays animal sounds received from the server. It is expected that by hearing these sounds, the animals will recognize the user's intentions and take appropriate action.

[0267] (Example 1)

[0268] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0269] Communication between animals and humans is often fraught with difficulties in understanding emotions and intentions. This makes it challenging to assess an animal's condition and take appropriate action. Furthermore, it is difficult for humans to interpret animal vocalizations as meaningful information and to effectively communicate their own messages to animals.

[0270] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0271] In this invention, the server includes means for analyzing animal vocal information to identify emotions and intentions, means for translating the identified information into language, and means for converting it into animal-understandable speech and outputting it. This makes it possible to accurately understand the emotions and intentions of animals and to effectively convey messages from humans to animals.

[0272] "Auditory information" refers to information that is recorded from sounds emitted by animals or humans and treated as digital data.

[0273] An "information processing device" is a server or computer system that analyzes audio information and performs specific processing.

[0274] A "terminal device" is a device that a user directly operates to display information or play audio.

[0275] "Natural language processing" refers to a technology for translating audio information into language, and it is a function that uses artificial intelligence to analyze meaning and intent.

[0276] "Animal-ready audio" refers to audio data generated in a format that animals can understand.

[0277] This invention is a system for effective communication between humans and animals using animal sounds. The user's terminal is equipped with hardware for recording sound, such as a microphone. The user can use the sound recording function to collect sounds emitted by animals, such as pets. This information is transmitted from the terminal to an information processing device (server) via the internet.

[0278] The server receives audio information and analyzes it using a generative AI model. Specifically, it uses natural language processing capabilities to identify the animal's emotions and intentions from the audio data. This involves technologies such as deep learning algorithms. During this process, characteristic audio patterns specific to each animal species are analyzed.

[0279] The identified emotions and intentions are translated into a language easily understood by the user and sent to the terminal device. The user can check the translation results on the terminal's display. Furthermore, when the user enters a message they want to convey to an animal into the terminal, the message is analyzed by a server and converted into animal-readable speech. The terminal then plays the converted speech to convey the user's intentions to the animal.

[0280] As a specific example, it can be mentioned that the user inputs a prompt sentence such as "Analyze the barking sound of a dog and translate it into a phrase that can understand emotions". With this prompt, the server can analyze the barking sound of the dog, identify the intention such as "want to play", and inform the user. As a result, animal lovers and pet owners can understand the emotions of animals more deeply and smooth their communication in daily life.

[0281] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0282] Step 1:

[0283] The user uses the recording function of the terminal to capture the voice of the animal. In this step, the user uses the microphone equipped on the terminal to record the barking sound of an animal, such as a pet dog. The recorded voice data is obtained as an input.

[0284] Step 2:

[0285] The terminal transmits the recorded voice data to the server via the Internet. In this transmission, the voice data is compressed or encoded as a digital file and transmitted by a secure communication protocol (such as SSL / TLS). As a result, the server receives the voice data as an input.

[0286] Step 3:

[0287] The server analyzes the received voice data. In this analysis process, first, the voice data is input into a deep learning model to identify the emotions and intentions of the animal. In this process, a generative AI model is used to extract the features of the voice, and based on that, the emotions and intentions are estimated. As a result of the analysis, an intention such as "want to play" is obtained as an output.

[0288] Step 4:

[0289] The server translates the analysis results into a language that the user can easily understand. This translation step converts identified emotions and intentions into natural language text. A generative AI model is used for translation, and the result is output as a text message.

[0290] Step 5:

[0291] The server sends the translated result to the terminal. The terminal displays this result on its screen to inform the user. The user can then check the message displayed on the terminal and understand the animal's condition.

[0292] Step 6:

[0293] The user enters a message they want to convey to the animal into the device. In this step, the user uses the text input function to enter a message such as "Please wait a moment." This message is then received as input.

[0294] Step 7:

[0295] The terminal sends the entered message to the server. The server receives this message and converts it into animal sounds using a generation AI model. The resulting audio file is then output.

[0296] Step 8:

[0297] The device plays animal sounds transmitted from the server. During playback, the converted sounds are output from the device's speaker, allowing the user's intentions to be conveyed to the animal.

[0298] (Application Example 1)

[0299] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0300] In recent years, there has been a growing need to accurately understand the emotions and intentions of animals in communication between pets and their owners. However, there is a lack of technology to accurately analyze animal sounds and convey them in a way that is easily understood by humans. Furthermore, there is the challenge of conveying human messages in a way that animals can understand. In addition, there is a lack of systems in place at physical stores such as pet shops to support owners' purchasing decisions based on an understanding of the animals' condition.

[0301] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0302] In this invention, the server includes means for analyzing animal vocal information and identifying the animal's emotions or intentions; means for translating the identified emotions or intentions into natural language and transmitting them to an information terminal; and means for converting the natural language into a form that the animal can understand and outputting it to the animal. This facilitates smooth communication between animals and their owners, improves the customer experience in physical stores, and enables effective product recommendations.

[0303] "Animal vocal information" refers to digitized data of sounds emitted by animals. This data serves as a basis for analyzing animals' emotions and intentions.

[0304] A "central processing unit" refers to a computer system that receives, analyzes, and translates audio information. This device interacts with terminals via a network.

[0305] "Natural language" refers to the language that humans use on a daily basis, and is used to communicate the emotions and intentions of animals in a way that is easily understood by humans.

[0306] An "information terminal" refers to a device used by a user to receive and display information. Specifically, this includes smartphones and tablets.

[0307] "Products for animals" refers to products that cater to the characteristics and needs of animals. Specifically, it includes toys, food, care products, etc., and plays a role in assisting such proposals.

[0308] "Generative AI model" refers to an artificial intelligence framework that learns from data and executes tasks such as animal voice analysis and natural language generation. This is used to support smooth communication between animals and humans.

[0309] To realize this invention, the server and the terminal play a central role in the system. The server receives the voice information of animals and analyzes the voice using the generative AI model. In this analysis process, an algorithm for identifying emotions and intentions from the voice characteristics of animals is used. Specifically, based on the frequency components and rhythm patterns of the voice, states such as "want to play" and "feeling anxious" of the animal are estimated.

[0310] After the analysis is completed, the server translates these estimation results into natural language. The translation result is directly sent to the terminal. The terminal is the user's smartphone or tablet and has the function of displaying this translation result on the screen. The displayed information helps the user quickly understand the state of the pet and take appropriate actions.

[0311] On the other hand, when the user inputs a message into the terminal, the terminal sends the message to the server again. The server synthesizes the input human language into a voice form that animals can understand. This synthesis technology generally includes, for example, the function of a voice synthesis engine. The synthesized voice is played from the terminal towards the animal, enabling smooth communication.

[0312] As a specific example, in a pet shop, through this system, customers are promoted to understand the mood of their pets in real time and immediately purchase the necessary products. At this time, the text used as an example of a prompt sentence is "Analyze the dog's voice, estimate the emotion, and display the result in Japanese."

[0313] This system is expected to improve the quality of communication between pets and their owners, and further enhance customer service at pet shops.

[0314] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0315] Step 1:

[0316] The device records animal sounds using its microphone and saves them as digital audio data. The user launches the device's recording application and captures their pet's sounds using the record button. This recorded data is sent to the server as initial input data.

[0317] Step 2:

[0318] The server analyzes the received audio data. Using a generative AI model, it analyzes the frequency components and temporal features of the audio to estimate the animal's emotions and intentions. The estimation results are output as specific emotional states such as "want to play" or "anxious" through data calculations.

[0319] Step 3:

[0320] The server translates the analyzed emotions and intentions into natural language. Using a generative AI model, the estimated emotions are converted into standard Japanese, generating a message that is easy for the user to understand. This content is then formatted as data to be sent to the device.

[0321] Step 4:

[0322] The device receives the translation results sent from the server and displays them on the screen. Through the device screen, the user can understand their pet's emotional state. For example, a message such as "Your pet wants to play" might be displayed.

[0323] Step 5:

[0324] The user enters the message they want to convey to their pet using the input interface built into the device. This input is then sent back to the server as data and processed into a communication format for the animal.

[0325] Step 6:

[0326] The server converts user input messages into speech that animals can understand. Using a generative AI model, it synthesizes the input Japanese into animal-friendly speech with specific frequencies and intonations. This result is then constructed as output data.

[0327] Step 7:

[0328] The device plays the converted audio data received from the server and emits the voice to the animal. This conveys the user's intentions to the pet. This process is completed when the animal actually changes its behavior in response to the message.

[0329] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0330] This invention provides a system that combines an emotion engine that analyzes animal sounds and recognizes user emotions. This system aims to improve communication between animals and humans through the cooperation of a server and a terminal. Furthermore, by using the emotion engine, it achieves more appropriate interaction while considering the user's emotional state.

[0331] First, the device records the voices of both the user and the animal. During this process, the user's voice is analyzed by an emotion engine to identify the user's emotions, while the animal's voice is sent to the server.

[0332] After receiving animal voice data, the server uses an AI engine to analyze the data. This analysis identifies the animal's emotions and intentions, and then the process of translating this into human language begins.

[0333] Next, the emotion engine processes the user's emotional data and suggests the optimal communication content to convey to the animal. Specifically, if the user is feeling stressed, the content of the interaction with the animal can be adjusted to promote mutual relaxation.

[0334] Based on the translated animal's emotions or intentions, and suggestions from the emotion engine, the server sends information to the terminal. The terminal displays this information to the user. Based on this information, the user can decide how to respond to the animal.

[0335] Furthermore, when a user enters their own words, those words are sent back to the server and converted into an appropriate voice format for the animal. This ensures that the message is delivered to the animal and communication is completed.

[0336] As a concrete example, consider a scenario where a user is relaxing with their pet cat. If the cat makes a sound indicating it wants attention, the system will display the most appropriate interaction method based on the user's current emotional state.

[0337] This system allows users to interact with animals while harmonizing their own emotions with the animals' states, thereby improving their quality of life.

[0338] The following describes the processing flow.

[0339] Step 1:

[0340] The device simultaneously records audio data from both the user and the animal. Recording begins when the user presses the "Start Recording" button, and the device captures the data using its built-in microphone.

[0341] Step 2:

[0342] The device splits the recorded data into user voice data and animal voice data, saving them as temporary files. This operation is necessary to analyze the two voices individually.

[0343] Step 3:

[0344] The emotion engine analyzes the user's voice data to identify the user's emotional state. This process estimates emotions by evaluating factors such as tone, speed, and language patterns within the voice.

[0345] Step 4:

[0346] The device sends animal sound data to the server. A secure communication protocol is used for data transmission, and it is ensured that the data reaches the server accurately.

[0347] Step 5:

[0348] The server uses an AI engine to analyze the animal's voice data it receives. The server detects patterns in the animal's vocalizations and identifies the emotions and intentions they convey.

[0349] Step 6:

[0350] The server translates the analysis results into human language, expressing the animal's emotions and intentions. Simultaneously, it considers the user's emotional state to generate suggestions from the emotion engine.

[0351] Step 7:

[0352] The server sends the translation results and suggestions from the engine to the terminal. The terminal receives the information and promptly notifies the user.

[0353] Step 8:

[0354] The device displays the information it receives to the user. Based on the displayed information, the user can decide on appropriate actions and words for the animal.

[0355] Step 9:

[0356] The user enters a response into the terminal, and the terminal sends that input data to the server. This data is a message that should be understood by animals.

[0357] Step 10:

[0358] The server converts the user's words into an animal-readable voice format and sends this voice to the device. The device then plays this voice and communicates with the animal.

[0359] Thus, this system accurately recognizes the emotions of both the user and the animal, and highly optimizes communication.

[0360] (Example 2)

[0361] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0362] In animal-human communication, there is a need for a system that can accurately understand the animal's emotions and intentions, and enable appropriate human responses based on that understanding. However, conventional systems have the problem of low accuracy in identifying emotions from animal sounds and the inability to suggest communication that takes the user's emotions into consideration. Therefore, there is a need to provide a system that can realize ideal interaction between animals and humans and improve their quality of life.

[0363] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0364] In this invention, the server includes means for analyzing animal vocal information and identifying its emotions and intentions, means for converting the identified emotions and intentions into human language, and means for detecting the user's vocal emotions and suggesting a communication method that corresponds to the user's emotions. This enables a highly accurate understanding of the animal's emotions and intentions, as well as appropriate interaction that takes the user's emotions into consideration.

[0365] "Auditory information" refers to sound data obtained from animals or users, including elements such as pitch, intensity, and temporal changes in sound.

[0366] A "processing device" refers to a computer system that analyzes audio data to identify the emotions and intentions of animals.

[0367] "Emotion or intention" refers to the mental or behavioral state indicated by the sounds an animal makes, as determined by analysis.

[0368] "Human language" refers to the natural forms of language used to translate the intentions and emotions of animals, and which are understandable to humans.

[0369] A "terminal device" refers to a device that serves as an interface with the end user, allowing the user to receive and input voice information.

[0370] "Vocal emotion" refers to the emotional state emanating from the user's voice, including emotional responses such as stress and relaxation.

[0371] "Communication methods" refer to specific behaviors and ways of dialogue proposed to facilitate interaction with animals.

[0372] A "generative AI model" refers to an artificial intelligence model used for analyzing and translating speech data, and is the algorithm that underpins the entire process.

[0373] A "prompt statement" refers to a trigger statement that is input into the generation AI model. Based on this, the model operates and generates results.

[0374] This invention is a system for enhancing communication between animals and humans, where a server, terminal, and user work together seamlessly. The specific configuration for carrying out this invention is shown below.

[0375] First, the device acquires the voices of both the user and the animal. The device is a smartphone or a dedicated device that collects voice data in real time using its built-in microphone. The user's voice data is analyzed by an emotion engine within the device, and the user's emotions are identified, for example, as "peaceful" or "exhilarated." The animal's voice data is formatted and then sent to a server via the internet.

[0376] The server receives audio data and then analyzes it using an AI engine. Specifically, it uses generative AI models such as TensorFlow and PyTorch to identify emotions and intentions from animal voices. When it recognizes a state such as "excited" in the animal, it translates it into human language. This translated information is then sent to the terminal.

[0377] The user determines how to interact with the animal based on the information provided by the device. Furthermore, if the user has something they want to communicate to the animal, they can input it into the device. The input is then sent back to the server and converted into an animal-friendly voice format. For example, a message like "Let's play together" would be output in a voice customized for the animal.

[0378] As a concrete example, consider a scenario where a user is spending time with their pet dog. If the dog makes a sound indicating it wants to go outside, the system suggests an interaction method based on the user's current emotional state, such as "taking the dog for a walk with leadership." This system allows users to communicate in a way that harmonizes their own emotions while understanding the animal's state.

[0379] An example of a prompt message might be, "Analyze the sound of a dog barking and translate its emotion." This allows the system to function comprehensively and play a role in improving the quality of life for both animals and humans.

[0380] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0381] Step 1:

[0382] The device acquires user and animal voices in real time. When the user uses the device's microphone to collect voices, the audio data is immediately digitized and pre-processed to analyze the user's emotions. The input is the user's and animal's voices, and the output is digitized audio data. Specific operations include noise reduction and conversion of the audio to the time domain.

[0383] Step 2:

[0384] The device transmits the user's voice data to its built-in emotion engine. The emotion engine uses a generative AI model to analyze the characteristics of the voice and identify the user's emotional state, such as "relaxed" or "stressed." The input is the digitized user's voice, and the output is the identified emotional state. Specifically, the process involves spectrogram conversion and comparison with the emotion model.

[0385] Step 3:

[0386] The terminal transmits animal voice data to the server. For transmission, the voice data is effectively packaged and delivered to the server via a secure communication method. The input is digitized animal voice, and the output is the packaged data sent to the server. Specific operations include data compression and transfer using a secure protocol.

[0387] Step 4:

[0388] The server analyzes the received animal voice data using an AI engine. The generative AI model used here evaluates the animal's voice patterns and identifies its emotions and intentions. The input is the animal voice package received by the server, and the output is the identified emotions and intentions of the animal. Specifically, the process involves filtering the voice waveform and applying an emotion identification algorithm.

[0389] Step 5:

[0390] The server translates the identified animal's emotions or intentions into human language and sends it to the terminal. The translated information is provided in a format that is easy for the user to understand. The input is the identified animal's emotions or intentions, and the output is the translation into human language. Specifically, text generation is performed using a natural language processing module.

[0391] Step 6:

[0392] The user decides how to interact with the animal based on its state and emotions presented by the device. If necessary, the user interactively determines a course of action. The input is translated animal emotion information, and the output is the user's decision to act. The specific actions involve the user's decision-making process based on the provided information.

[0393] Step 7:

[0394] When a user wants to send a message to an animal, they type the words into the device. These words are sent to a server and converted into an animal-readable audio format. The input is text information entered by the user, and the output is played back on the device as audio for the animal. Specifically, text-to-speech technology is used for speech generation.

[0395] (Application Example 2)

[0396] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0397] Smooth communication between animals and humans is crucial for deepening mutual understanding, especially in relationships with pets. However, since animals cannot directly communicate with humans, accurately understanding their emotions and intentions is difficult. Furthermore, teaching animals appropriate communication methods based on human emotional states is an even more complex challenge. There is a need to solve these problems and develop safe and effective means of facilitating interaction between visitors and animals in pet shops and veterinary clinics.

[0398] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0399] In this invention, the server includes means for analyzing animal voice data to identify emotions or intentions, means for analyzing human emotion data to recommend optimal communication, and means for proposing interaction methods suitable for both animals and humans. This enables communication in which animals and humans can mutually understand each other's emotions and intentions.

[0400] "Animal sound data" refers to digital recordings of sounds emitted by animals.

[0401] A "server" is a computing device that receives and analyzes animal and human voice data.

[0402] "Means for identifying emotions or intentions" refers to technologies and algorithms for analyzing and revealing the emotions and behavioral intentions of animals from received audio data.

[0403] "Human emotion data" refers to data used to identify a person's emotional state based on their voice and other biometric information.

[0404] "Means of recommending optimal communication" refers to technologies and systems that propose methods for smooth interaction between humans and animals based on analyzed emotional data.

[0405] A "terminal" is a device that displays information sent from a server to the user and also accepts input from the user.

[0406] "Translation means" are technologies or devices that translate animal emotions or intentions into language that humans can understand, or vice versa.

[0407] "Means of proposing methods of interaction" refer to technologies and functions that present optimal methods of interaction while taking into account the emotions of animals and humans.

[0408] The system for implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user.

[0409] First, the device is equipped with microphones to record animal and user voices. The recorded audio data is sent to a server in digital format. The server uses an advanced analysis engine to identify the emotions and intentions of the animal's voice. The software used includes natural language processing libraries and speech sentiment analysis libraries (e.g., Python's NLTK and OpenAI models).

[0410] Next, the server uses an emotion recognition engine (e.g., Microsoft Azure Emotion API) to analyze the user's voice and recognize their emotions. This emotion data is then analyzed in conjunction with animal emotion data and used in a process to suggest the most appropriate communication method. The recommendations generated by the AI ​​model are presented to the user visually through the device's display.

[0411] Users can view suggested methods via their device and respond to animals using their own actions and voice. The voice input and choices from the user are sent back to the server and converted into speech that animals can understand. This conversion uses text-to-speech technology (e.g., Google Text-to-Speech).

[0412] As a concrete example, let's consider an application in a pet shop. When a customer is interacting with a cat in the store, if the cat makes a sound indicating it wants to play, the system will use the user's emotional state to suggest the best way for the user to interact with the cat. For example, a user who is feeling stressed will be offered suggestions for conversation and play to help them relax with the cat. Examples of prompts in this case could include, "We will analyze the sounds the cat made to understand its emotions," or "We will suggest how the user should interact to help them relax."

[0413] This system offers an innovative means for better communication between animals and humans, and its implementation is particularly useful in places where contact with animals is frequent.

[0414] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0415] Step 1:

[0416] The device simultaneously records the voices of both the user and the animal. The input is real-time audio data obtained through the device's microphone. This audio data is converted to a digital format and prepared for transmission to the server.

[0417] Step 2:

[0418] The server receives animal voice data sent from the terminal. The server uses an AI engine to analyze this input data, interpreting the animal's emotions and intentions. Here, a natural language processing library is used to process the data and convert it into human language for translation.

[0419] Step 3:

[0420] The server receives the user's voice data and uses an emotion engine to analyze the user's emotional state. The input voice data is converted into text data through the engine, and the user's emotions are output as numerical and textual information. This output is used for subsequent analysis.

[0421] Step 4:

[0422] The server determines the optimal communication method based on the analyzed animal's emotions and the user's emotions. A generative AI model is used here to create specific dialogue content as prompts. The output is information about the proposed interaction content.

[0423] Step 5:

[0424] The terminal receives information about the interaction content sent from the server and visualizes it for the user. Specific action instructions and communication methods displayed on the terminal are output in a format that the user can easily understand.

[0425] Step 6:

[0426] The user communicates with the animal according to the information presented through the device. The user's input (e.g., selected communication mode) is resent from the device to the server and proceeds to the step where it is converted into voice for the animal.

[0427] Step 7:

[0428] The server converts the user's input into an audio format that animals can understand and outputs it to the animals via the terminal. Here, the text-to-speech conversion process takes place, resulting in output data for directly approaching the animals.

[0429] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0430] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0431] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0432] [Third Embodiment]

[0433] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0434] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0435] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0436] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0437] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0438] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0439] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0440] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0441] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0442] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0443] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0444] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0445] This invention is a system for facilitating communication between humans and animals by utilizing animal sounds. This system operates with a server and terminals working together to analyze animal sound data, convey its content to humans, and also transmit messages from humans to animals in an understandable format.

[0446] First, the device records the animal's voice. For example, a user might use their smartphone to capture the sound of their pet dog barking. This recorded audio data is then sent to a server via the internet.

[0447] Next, the server analyzes the received audio data using an AI engine. Here, the server identifies what emotions or intentions the animal is currently experiencing based on the animal's unique vocal characteristics. This process allows the server to estimate states such as "wanting to play" or "feeling anxious."

[0448] Based on the analysis results, the server translates the animal's emotions and intentions into natural language. This process allows users to understand the animal's state in a format they can easily comprehend. The translated results are sent to the terminal and displayed to the user.

[0449] When a user enters a message they want to convey to an animal, the device sends that message to a server. The server converts human language into speech that animals can understand. This speech is then played back on the device and conveyed to the animal.

[0450] The system described above can be used in a specific scenario, such as when a user spends a holiday at home with their dog. When the dog makes a sound indicating it wants to play, the user can quickly understand this and respond at the appropriate time.

[0451] Thus, the system of the present invention can be used to facilitate effective communication with animals in a variety of situations. For animal lovers and pet owners, it is a valuable tool that allows them to gain a deeper understanding of the animal's psychological state and reflect that understanding in their behavior.

[0452] The following describes the processing flow.

[0453] Step 1:

[0454] The user activates the device's recording function and prepares to record animal sounds. The recording process begins when the user presses the "Start Recording" button.

[0455] Step 2:

[0456] The device saves the recorded animal audio data as a temporary file. In this process, the audio is captured as digital data and converted to a format that can be transmitted later.

[0457] Step 3:

[0458] The device transmits stored animal audio data to the server via an internet connection. A secure protocol is used for data transmission to ensure that the audio is delivered accurately and safely to the server.

[0459] Step 4:

[0460] The server analyzes the received audio data. The server's AI engine works to analyze the audio patterns in order to determine the emotions and intentions from the animal's voice.

[0461] Step 5:

[0462] The server translates the animal's emotions or intentions into human language based on the analysis results. This translation is then converted into easy-to-understand text and formatted in a way that is easy for the user to comprehend.

[0463] Step 6:

[0464] The server sends the translated text back to the terminal. The terminal prepares to display this information on the screen for the user to see.

[0465] Step 7:

[0466] The user checks the translation displayed on the device and enters a response. For example, they might enter the message, "Are you hungry?"

[0467] Step 8:

[0468] The terminal sends the message entered by the user to the server. At this point, the message needs to be translated so that the animal can understand it, and is therefore processed by the server.

[0469] Step 9:

[0470] The server converts the received user message into an audio format that animals can understand. The translated audio data is then sent to the device.

[0471] Step 10:

[0472] The device plays animal sounds received from the server. It is expected that by hearing these sounds, the animals will recognize the user's intentions and take appropriate action.

[0473] (Example 1)

[0474] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0475] Communication between animals and humans is often fraught with difficulties in understanding emotions and intentions. This makes it challenging to assess an animal's condition and take appropriate action. Furthermore, it is difficult for humans to interpret animal vocalizations as meaningful information and to effectively communicate their own messages to animals.

[0476] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0477] In this invention, the server includes means for analyzing animal vocal information to identify emotions and intentions, means for translating the identified information into language, and means for converting it into animal-understandable speech and outputting it. This makes it possible to accurately understand the emotions and intentions of animals and to effectively convey messages from humans to animals.

[0478] "Auditory information" refers to information that is recorded from sounds emitted by animals or humans and treated as digital data.

[0479] An "information processing device" is a server or computer system that analyzes audio information and performs specific processing.

[0480] A "terminal device" is a device that a user directly operates to display information or play audio.

[0481] "Natural language processing" refers to a technology for translating audio information into language, and it is a function that uses artificial intelligence to analyze meaning and intent.

[0482] "Animal-ready audio" refers to audio data generated in a format that animals can understand.

[0483] This invention is a system for effective communication between humans and animals using animal sounds. The user's terminal is equipped with hardware for recording sound, such as a microphone. The user can use the sound recording function to collect sounds emitted by animals, such as pets. This information is transmitted from the terminal to an information processing device (server) via the internet.

[0484] The server receives audio information and analyzes it using a generative AI model. Specifically, it uses natural language processing capabilities to identify the animal's emotions and intentions from the audio data. This involves technologies such as deep learning algorithms. During this process, characteristic audio patterns specific to each animal species are analyzed.

[0485] The identified emotions and intentions are translated into a language easily understood by the user and sent to the terminal device. The user can check the translation results on the terminal's display. Furthermore, when the user enters a message they want to convey to an animal into the terminal, the message is analyzed by a server and converted into animal-readable speech. The terminal then plays the converted speech to convey the user's intentions to the animal.

[0486] A concrete example is when a user enters a prompt such as, "Analyze the dog's bark and translate it into a phrase that expresses its emotion." This prompt allows the server to analyze the dog's bark, identify its intention (e.g., "I want to play"), and inform the user. This enables animal lovers and pet owners to better understand their animals' emotions and facilitate smoother communication in daily life.

[0487] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0488] Step 1:

[0489] The user captures animal sounds using the device's recording function. In this step, the user uses the device's built-in microphone to record the barking of an animal, such as a pet dog. The recorded audio data is obtained as input.

[0490] Step 2:

[0491] The device sends the recorded audio data to the server over the internet. During this transmission, the audio data is compressed or encoded as a digital file and sent using a secure communication protocol (e.g., SSL / TLS). The server then receives the audio data as input.

[0492] Step 3:

[0493] The server analyzes the received audio data. In this analysis process, the audio data is first input into a deep learning model to identify the animal's emotions and intentions. This process uses a generative AI model to extract audio features and estimate emotions and intentions based on them. As a result of the analysis, an intention such as "I want to play" is output.

[0494] Step 4:

[0495] The server translates the analysis results into a language that the user can easily understand. This translation step converts identified emotions and intentions into natural language text. A generative AI model is used for translation, and the result is output as a text message.

[0496] Step 5:

[0497] The server sends the translated result to the terminal. The terminal displays this result on its screen to inform the user. The user can then check the message displayed on the terminal and understand the animal's condition.

[0498] Step 6:

[0499] The user enters a message they want to convey to the animal into the device. In this step, the user uses the text input function to enter a message such as "Please wait a moment." This message is then received as input.

[0500] Step 7:

[0501] The terminal sends the entered message to the server. The server receives this message and converts it into animal sounds using a generation AI model. The resulting audio file is then output.

[0502] Step 8:

[0503] The device plays animal sounds transmitted from the server. During playback, the converted sounds are output from the device's speaker, allowing the user's intentions to be conveyed to the animal.

[0504] (Application Example 1)

[0505] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0506] In recent years, there has been a growing need to accurately understand the emotions and intentions of animals in communication between pets and their owners. However, there is a lack of technology to accurately analyze animal sounds and convey them in a way that is easily understood by humans. Furthermore, there is the challenge of conveying human messages in a way that animals can understand. In addition, there is a lack of systems in place at physical stores such as pet shops to support owners' purchasing decisions based on an understanding of the animals' condition.

[0507] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0508] In this invention, the server includes means for analyzing animal vocal information and identifying the animal's emotions or intentions; means for translating the identified emotions or intentions into natural language and transmitting them to an information terminal; and means for converting the natural language into a form that the animal can understand and outputting it to the animal. This facilitates smooth communication between animals and their owners, improves the customer experience in physical stores, and enables effective product recommendations.

[0509] "Animal vocal information" refers to digitized data of sounds emitted by animals. This data serves as a basis for analyzing animals' emotions and intentions.

[0510] A "central processing unit" refers to a computer system that receives, analyzes, and translates audio information. This device interacts with terminals via a network.

[0511] "Natural language" refers to the language that humans use on a daily basis, and is used to communicate the emotions and intentions of animals in a way that is easily understood by humans.

[0512] An "information terminal" refers to a device used by a user to receive and display information. Specifically, this includes smartphones and tablets.

[0513] "Animal products" refer to products tailored to the characteristics and needs of animals. Specifically, this includes toys, food, and care products, and the role is to support the recommendation of such products.

[0514] A "generative AI model" refers to an artificial intelligence framework that learns from data and performs tasks such as analyzing animal voices and generating natural language. It is used to support smooth communication between animals and humans.

[0515] To realize this invention, the server and terminal play a central role in the system. The server receives animal vocal information and analyzes it using a generative AI model. This analysis process uses an algorithm that identifies emotions and intentions from the animal's vocal characteristics. Specifically, it estimates the animal's state, such as "wanting to play" or "feeling anxious," based on the frequency components and rhythmic patterns of the vocals.

[0516] Once the analysis is complete, the server translates these estimation results into natural language. The translated results are then sent directly to the terminal. The terminal is the user's smartphone or tablet, which has the capability to display these translated results on its screen. The displayed information helps the user quickly understand their pet's condition and take appropriate action.

[0517] On the other hand, when a user enters a message into the device, the device sends that message back to the server. The server synthesizes the entered human language into speech that animals can understand. This synthesis technology typically includes the functions of a speech synthesis engine. The synthesized speech is played back from the device to the animal, enabling smooth communication.

[0518] As a concrete example, in pet shops, this system would be used to enable customers to understand their pet's feelings in real time and instantly purchase the necessary products. In this case, an example of a prompt text would be, "Analyze the dog's voice, estimate its emotions, and display the result in Japanese."

[0519] This system is expected to improve the quality of communication between pets and their owners, and further enhance customer service at pet shops.

[0520] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0521] Step 1:

[0522] The device records animal sounds using its microphone and saves them as digital audio data. The user launches the device's recording application and captures their pet's sounds using the record button. This recorded data is sent to the server as initial input data.

[0523] Step 2:

[0524] The server analyzes the received audio data. Using a generative AI model, it analyzes the frequency components and temporal features of the audio to estimate the animal's emotions and intentions. The estimation results are output as specific emotional states such as "want to play" or "anxious" through data calculations.

[0525] Step 3:

[0526] The server translates the analyzed emotions and intentions into natural language. Using a generative AI model, the estimated emotions are converted into standard Japanese, generating a message that is easy for the user to understand. This content is then formatted as data to be sent to the device.

[0527] Step 4:

[0528] The device receives the translation results sent from the server and displays them on the screen. Through the device screen, the user can understand their pet's emotional state. For example, a message such as "Your pet wants to play" might be displayed.

[0529] Step 5:

[0530] The user enters the message they want to convey to their pet using the input interface built into the device. This input is then sent back to the server as data and processed into a communication format for the animal.

[0531] Step 6:

[0532] The server converts user input messages into speech that animals can understand. Using a generative AI model, it synthesizes the input Japanese into animal-friendly speech with specific frequencies and intonations. This result is then constructed as output data.

[0533] Step 7:

[0534] The device plays the converted audio data received from the server and emits the voice to the animal. This conveys the user's intentions to the pet. This process is completed when the animal actually changes its behavior in response to the message.

[0535] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0536] This invention provides a system that combines an emotion engine that analyzes animal sounds and recognizes user emotions. This system aims to improve communication between animals and humans through the cooperation of a server and a terminal. Furthermore, by using the emotion engine, it achieves more appropriate interaction while considering the user's emotional state.

[0537] First, the device records the voices of both the user and the animal. During this process, the user's voice is analyzed by an emotion engine to identify the user's emotions, while the animal's voice is sent to the server.

[0538] After receiving animal voice data, the server uses an AI engine to analyze the data. This analysis identifies the animal's emotions and intentions, and then the process of translating this into human language begins.

[0539] Next, the emotion engine processes the user's emotional data and suggests the optimal communication content to convey to the animal. Specifically, if the user is feeling stressed, the content of the interaction with the animal can be adjusted to promote mutual relaxation.

[0540] Based on the translated animal's emotions or intentions, and suggestions from the emotion engine, the server sends information to the terminal. The terminal displays this information to the user. Based on this information, the user can decide how to respond to the animal.

[0541] Furthermore, when a user enters their own words, those words are sent back to the server and converted into an appropriate voice format for the animal. This ensures that the message is delivered to the animal and communication is completed.

[0542] As a concrete example, consider a scenario where a user is relaxing with their pet cat. If the cat makes a sound indicating it wants attention, the system will display the most appropriate interaction method based on the user's current emotional state.

[0543] This system allows users to interact with animals while harmonizing their own emotions with the animals' states, thereby improving their quality of life.

[0544] The following describes the processing flow.

[0545] Step 1:

[0546] The device simultaneously records audio data from both the user and the animal. Recording begins when the user presses the "Start Recording" button, and the device captures the data using its built-in microphone.

[0547] Step 2:

[0548] The device splits the recorded data into user voice data and animal voice data, saving them as temporary files. This operation is necessary to analyze the two voices individually.

[0549] Step 3:

[0550] The emotion engine analyzes the user's voice data to identify the user's emotional state. This process estimates emotions by evaluating factors such as tone, speed, and language patterns within the voice.

[0551] Step 4:

[0552] The device sends animal sound data to the server. A secure communication protocol is used for data transmission, and it is ensured that the data reaches the server accurately.

[0553] Step 5:

[0554] The server uses an AI engine to analyze the animal's voice data it receives. The server detects patterns in the animal's vocalizations and identifies the emotions and intentions they convey.

[0555] Step 6:

[0556] The server translates the analysis results into human language, expressing the animal's emotions and intentions. Simultaneously, it considers the user's emotional state to generate suggestions from the emotion engine.

[0557] Step 7:

[0558] The server sends the translation results and suggestions from the engine to the terminal. The terminal receives the information and promptly notifies the user.

[0559] Step 8:

[0560] The device displays the information it receives to the user. Based on the displayed information, the user can decide on appropriate actions and words for the animal.

[0561] Step 9:

[0562] The user enters a response into the terminal, and the terminal sends that input data to the server. This data is a message that should be understood by animals.

[0563] Step 10:

[0564] The server converts the user's words into an animal-readable voice format and sends this voice to the device. The device then plays this voice and communicates with the animal.

[0565] Thus, this system accurately recognizes the emotions of both the user and the animal, and highly optimizes communication.

[0566] (Example 2)

[0567] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0568] In animal-human communication, there is a need for a system that can accurately understand the animal's emotions and intentions, and enable appropriate human responses based on that understanding. However, conventional systems have the problem of low accuracy in identifying emotions from animal sounds and the inability to suggest communication that takes the user's emotions into consideration. Therefore, there is a need to provide a system that can realize ideal interaction between animals and humans and improve their quality of life.

[0569] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0570] In this invention, the server includes means for analyzing animal vocal information and identifying its emotions and intentions, means for converting the identified emotions and intentions into human language, and means for detecting the user's vocal emotions and suggesting a communication method that corresponds to the user's emotions. This enables a highly accurate understanding of the animal's emotions and intentions, as well as appropriate interaction that takes the user's emotions into consideration.

[0571] "Auditory information" refers to sound data obtained from animals or users, including elements such as pitch, intensity, and temporal changes in sound.

[0572] A "processing device" refers to a computer system that analyzes audio data to identify the emotions and intentions of animals.

[0573] "Emotion or intention" refers to the mental or behavioral state indicated by the sounds an animal makes, as determined by analysis.

[0574] "Human language" refers to the natural forms of language used to translate the intentions and emotions of animals, and which are understandable to humans.

[0575] A "terminal device" refers to a device that serves as an interface with the end user, allowing the user to receive and input voice information.

[0576] "Vocal emotion" refers to the emotional state emanating from the user's voice, including emotional responses such as stress and relaxation.

[0577] "Communication methods" refer to specific behaviors and ways of dialogue proposed to facilitate interaction with animals.

[0578] A "generative AI model" refers to an artificial intelligence model used for analyzing and translating speech data, and is the algorithm that underpins the entire process.

[0579] A "prompt statement" refers to a trigger statement that is input into the generation AI model. Based on this, the model operates and generates results.

[0580] This invention is a system for enhancing communication between animals and humans, where a server, terminal, and user work together seamlessly. The specific configuration for carrying out this invention is shown below.

[0581] First, the device acquires the voices of both the user and the animal. The device is a smartphone or a dedicated device that collects voice data in real time using its built-in microphone. The user's voice data is analyzed by an emotion engine within the device, and the user's emotions are identified, for example, as "peaceful" or "exhilarated." The animal's voice data is formatted and then sent to a server via the internet.

[0582] The server receives audio data and then analyzes it using an AI engine. Specifically, it uses generative AI models such as TensorFlow and PyTorch to identify emotions and intentions from animal voices. When it recognizes a state such as "excited" in the animal, it translates it into human language. This translated information is then sent to the terminal.

[0583] The user determines how to interact with the animal based on the information provided by the device. Furthermore, if the user has something they want to communicate to the animal, they can input it into the device. The input is then sent back to the server and converted into an animal-friendly voice format. For example, a message like "Let's play together" would be output in a voice customized for the animal.

[0584] As a concrete example, consider a scenario where a user is spending time with their pet dog. If the dog makes a sound indicating it wants to go outside, the system suggests an interaction method based on the user's current emotional state, such as "taking the dog for a walk with leadership." This system allows users to communicate in a way that harmonizes their own emotions while understanding the animal's state.

[0585] An example of a prompt message might be, "Analyze the sound of a dog barking and translate its emotion." This allows the system to function comprehensively and play a role in improving the quality of life for both animals and humans.

[0586] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0587] Step 1:

[0588] The device acquires user and animal voices in real time. When the user uses the device's microphone to collect voices, the audio data is immediately digitized and pre-processed to analyze the user's emotions. The input is the user's and animal's voices, and the output is digitized audio data. Specific operations include noise reduction and conversion of the audio to the time domain.

[0589] Step 2:

[0590] The device transmits the user's voice data to its built-in emotion engine. The emotion engine uses a generative AI model to analyze the characteristics of the voice and identify the user's emotional state, such as "relaxed" or "stressed." The input is the digitized user's voice, and the output is the identified emotional state. Specifically, the process involves spectrogram conversion and comparison with the emotion model.

[0591] Step 3:

[0592] The terminal transmits animal voice data to the server. For transmission, the voice data is effectively packaged and delivered to the server via a secure communication method. The input is digitized animal voice, and the output is the packaged data sent to the server. Specific operations include data compression and transfer using a secure protocol.

[0593] Step 4:

[0594] The server analyzes the received animal voice data using an AI engine. The generative AI model used here evaluates the animal's voice patterns and identifies its emotions and intentions. The input is the animal voice package received by the server, and the output is the identified emotions and intentions of the animal. Specifically, the process involves filtering the voice waveform and applying an emotion identification algorithm.

[0595] Step 5:

[0596] The server translates the identified animal's emotions or intentions into human language and sends it to the terminal. The translated information is provided in a format that is easy for the user to understand. The input is the identified animal's emotions or intentions, and the output is the translation into human language. Specifically, text generation is performed using a natural language processing module.

[0597] Step 6:

[0598] The user decides how to interact with the animal based on its state and emotions presented by the device. If necessary, the user interactively determines a course of action. The input is translated animal emotion information, and the output is the user's decision to act. The specific actions involve the user's decision-making process based on the provided information.

[0599] Step 7:

[0600] When a user wants to send a message to an animal, they type the words into the device. These words are sent to a server and converted into an animal-readable audio format. The input is text information entered by the user, and the output is played back on the device as audio for the animal. Specifically, text-to-speech technology is used for speech generation.

[0601] (Application Example 2)

[0602] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0603] Smooth communication between animals and humans is crucial for deepening mutual understanding, especially in relationships with pets. However, since animals cannot directly communicate with humans, accurately understanding their emotions and intentions is difficult. Furthermore, teaching animals appropriate communication methods based on human emotional states is an even more complex challenge. There is a need to solve these problems and develop safe and effective means of facilitating interaction between visitors and animals in pet shops and veterinary clinics.

[0604] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0605] In this invention, the server includes means for analyzing animal voice data to identify emotions or intentions, means for analyzing human emotion data to recommend optimal communication, and means for proposing interaction methods suitable for both animals and humans. This enables communication in which animals and humans can mutually understand each other's emotions and intentions.

[0606] "Animal sound data" refers to digital recordings of sounds emitted by animals.

[0607] A "server" is a computing device that receives and analyzes animal and human voice data.

[0608] "Means for identifying emotions or intentions" refers to technologies and algorithms for analyzing and revealing the emotions and behavioral intentions of animals from received audio data.

[0609] "Human emotion data" refers to data used to identify a person's emotional state based on their voice and other biometric information.

[0610] "Means of recommending optimal communication" refers to technologies and systems that propose methods for smooth interaction between humans and animals based on analyzed emotional data.

[0611] A "terminal" is a device that displays information sent from a server to the user and also accepts input from the user.

[0612] "Translation means" are technologies or devices that translate animal emotions or intentions into language that humans can understand, or vice versa.

[0613] "Means of proposing methods of interaction" refer to technologies and functions that present optimal methods of interaction while taking into account the emotions of animals and humans.

[0614] The system for implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user.

[0615] First, the device is equipped with microphones to record animal and user voices. The recorded audio data is sent to a server in digital format. The server uses an advanced analysis engine to identify the emotions and intentions of the animal's voice. The software used includes natural language processing libraries and speech sentiment analysis libraries (e.g., Python's NLTK and OpenAI models).

[0616] Next, the server uses an emotion recognition engine (e.g., Microsoft Azure Emotion API) to analyze the user's voice and recognize their emotions. This emotion data is then analyzed in conjunction with animal emotion data and used in a process to suggest the most appropriate communication method. The recommendations generated by the AI ​​model are presented to the user visually through the device's display.

[0617] Users can view suggested methods via their device and respond to animals using their own actions and voice. The voice input and choices from the user are sent back to the server and converted into speech that animals can understand. This conversion uses text-to-speech technology (e.g., Google Text-to-Speech).

[0618] As a concrete example, let's consider an application in a pet shop. When a customer is interacting with a cat in the store, if the cat makes a sound indicating it wants to play, the system will use the user's emotional state to suggest the best way for the user to interact with the cat. For example, a user who is feeling stressed will be offered suggestions for conversation and play to help them relax with the cat. Examples of prompts in this case could include, "We will analyze the sounds the cat made to understand its emotions," or "We will suggest how the user should interact to help them relax."

[0619] This system offers an innovative means for better communication between animals and humans, and its implementation is particularly useful in places where contact with animals is frequent.

[0620] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0621] Step 1:

[0622] The device simultaneously records the voices of both the user and the animal. The input is real-time audio data obtained through the device's microphone. This audio data is converted to a digital format and prepared for transmission to the server.

[0623] Step 2:

[0624] The server receives animal voice data sent from the terminal. The server uses an AI engine to analyze this input data, interpreting the animal's emotions and intentions. Here, a natural language processing library is used to process the data and convert it into human language for translation.

[0625] Step 3:

[0626] The server receives the user's voice data and uses an emotion engine to analyze the user's emotional state. The input voice data is converted into text data through the engine, and the user's emotions are output as numerical and textual information. This output is used for subsequent analysis.

[0627] Step 4:

[0628] The server determines the optimal communication method based on the analyzed animal's emotions and the user's emotions. A generative AI model is used here to create specific dialogue content as prompts. The output is information about the proposed interaction content.

[0629] Step 5:

[0630] The terminal receives information about the interaction content sent from the server and visualizes it for the user. Specific action instructions and communication methods displayed on the terminal are output in a format that the user can easily understand.

[0631] Step 6:

[0632] The user communicates with the animal according to the information presented through the device. The user's input (e.g., selected communication mode) is resent from the device to the server and proceeds to the step where it is converted into voice for the animal.

[0633] Step 7:

[0634] The server converts the user's input into an audio format that animals can understand and outputs it to the animals via the terminal. Here, the text-to-speech conversion process takes place, resulting in output data for directly approaching the animals.

[0635] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0636] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0637] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0638] [Fourth Embodiment]

[0639] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0640] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0641] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0642] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0643] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0644] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0645] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0646] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0647] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0648] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0649] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0650] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0651] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0652] This invention is a system for facilitating communication between humans and animals by utilizing animal sounds. This system operates with a server and terminals working together to analyze animal sound data, convey its content to humans, and also transmit messages from humans to animals in an understandable format.

[0653] First, the device records the animal's voice. For example, a user might use their smartphone to capture the sound of their pet dog barking. This recorded audio data is then sent to a server via the internet.

[0654] Next, the server analyzes the received audio data using an AI engine. Here, the server identifies what emotions or intentions the animal is currently experiencing based on the animal's unique vocal characteristics. This process allows the server to estimate states such as "wanting to play" or "feeling anxious."

[0655] Based on the analysis results, the server translates the animal's emotions and intentions into natural language. This process allows users to understand the animal's state in a format they can easily comprehend. The translated results are sent to the terminal and displayed to the user.

[0656] When a user enters a message they want to convey to an animal, the device sends that message to a server. The server converts human language into speech that animals can understand. This speech is then played back on the device and conveyed to the animal.

[0657] The system described above can be used in a specific scenario, such as when a user spends a holiday at home with their dog. When the dog makes a sound indicating it wants to play, the user can quickly understand this and respond at the appropriate time.

[0658] Thus, the system of the present invention can be used to facilitate effective communication with animals in a variety of situations. For animal lovers and pet owners, it is a valuable tool that allows them to gain a deeper understanding of the animal's psychological state and reflect that understanding in their behavior.

[0659] The following describes the processing flow.

[0660] Step 1:

[0661] The user activates the device's recording function and prepares to record animal sounds. The recording process begins when the user presses the "Start Recording" button.

[0662] Step 2:

[0663] The device saves the recorded animal audio data as a temporary file. In this process, the audio is captured as digital data and converted to a format that can be transmitted later.

[0664] Step 3:

[0665] The device transmits stored animal audio data to the server via an internet connection. A secure protocol is used for data transmission to ensure that the audio is delivered accurately and safely to the server.

[0666] Step 4:

[0667] The server analyzes the received audio data. The server's AI engine works to analyze the audio patterns in order to determine the emotions and intentions from the animal's voice.

[0668] Step 5:

[0669] The server translates the animal's emotions or intentions into human language based on the analysis results. This translation is then converted into easy-to-understand text and formatted in a way that is easy for the user to comprehend.

[0670] Step 6:

[0671] The server sends the translated text back to the terminal. The terminal prepares to display this information on the screen for the user to see.

[0672] Step 7:

[0673] The user checks the translation displayed on the device and enters a response. For example, they might enter the message, "Are you hungry?"

[0674] Step 8:

[0675] The terminal sends the message entered by the user to the server. At this point, the message needs to be translated so that the animal can understand it, and is therefore processed by the server.

[0676] Step 9:

[0677] The server converts the received user message into an audio format that animals can understand. The translated audio data is then sent to the device.

[0678] Step 10:

[0679] The device plays animal sounds received from the server. It is expected that by hearing these sounds, the animals will recognize the user's intentions and take appropriate action.

[0680] (Example 1)

[0681] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0682] Communication between animals and humans is often fraught with difficulties in understanding emotions and intentions. This makes it challenging to assess an animal's condition and take appropriate action. Furthermore, it is difficult for humans to interpret animal vocalizations as meaningful information and to effectively communicate their own messages to animals.

[0683] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0684] In this invention, the server includes means for analyzing animal vocal information to identify emotions and intentions, means for translating the identified information into language, and means for converting it into animal-understandable speech and outputting it. This makes it possible to accurately understand the emotions and intentions of animals and to effectively convey messages from humans to animals.

[0685] "Auditory information" refers to information that is recorded from sounds emitted by animals or humans and treated as digital data.

[0686] An "information processing device" is a server or computer system that analyzes audio information and performs specific processing.

[0687] A "terminal device" is a device that a user directly operates to display information or play audio.

[0688] "Natural language processing" refers to a technology for translating audio information into language, and it is a function that uses artificial intelligence to analyze meaning and intent.

[0689] "Animal-ready audio" refers to audio data generated in a format that animals can understand.

[0690] This invention is a system for effective communication between humans and animals using animal sounds. The user's terminal is equipped with hardware for recording sound, such as a microphone. The user can use the sound recording function to collect sounds emitted by animals, such as pets. This information is transmitted from the terminal to an information processing device (server) via the internet.

[0691] The server receives audio information and analyzes it using a generative AI model. Specifically, it uses natural language processing capabilities to identify the animal's emotions and intentions from the audio data. This involves technologies such as deep learning algorithms. During this process, characteristic audio patterns specific to each animal species are analyzed.

[0692] The identified emotions and intentions are translated into a language easily understood by the user and sent to the terminal device. The user can check the translation results on the terminal's display. Furthermore, when the user enters a message they want to convey to an animal into the terminal, the message is analyzed by a server and converted into animal-readable speech. The terminal then plays the converted speech to convey the user's intentions to the animal.

[0693] A concrete example is when a user enters a prompt such as, "Analyze the dog's bark and translate it into a phrase that expresses its emotion." This prompt allows the server to analyze the dog's bark, identify its intention (e.g., "I want to play"), and inform the user. This enables animal lovers and pet owners to better understand their animals' emotions and facilitate smoother communication in daily life.

[0694] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0695] Step 1:

[0696] The user captures animal sounds using the device's recording function. In this step, the user uses the device's built-in microphone to record the barking of an animal, such as a pet dog. The recorded audio data is obtained as input.

[0697] Step 2:

[0698] The device sends the recorded audio data to the server over the internet. During this transmission, the audio data is compressed or encoded as a digital file and sent using a secure communication protocol (e.g., SSL / TLS). The server then receives the audio data as input.

[0699] Step 3:

[0700] The server analyzes the received audio data. In this analysis process, the audio data is first input into a deep learning model to identify the animal's emotions and intentions. This process uses a generative AI model to extract audio features and estimate emotions and intentions based on them. As a result of the analysis, an intention such as "I want to play" is output.

[0701] Step 4:

[0702] The server translates the analysis results into a language that the user can easily understand. This translation step converts identified emotions and intentions into natural language text. A generative AI model is used for translation, and the result is output as a text message.

[0703] Step 5:

[0704] The server sends the translated result to the terminal. The terminal displays this result on its screen to inform the user. The user can then check the message displayed on the terminal and understand the animal's condition.

[0705] Step 6:

[0706] The user enters a message they want to convey to the animal into the device. In this step, the user uses the text input function to enter a message such as "Please wait a moment." This message is then received as input.

[0707] Step 7:

[0708] The terminal sends the entered message to the server. The server receives this message and converts it into animal sounds using a generation AI model. The resulting audio file is then output.

[0709] Step 8:

[0710] The device plays animal sounds transmitted from the server. During playback, the converted sounds are output from the device's speaker, allowing the user's intentions to be conveyed to the animal.

[0711] (Application Example 1)

[0712] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0713] In recent years, there has been a growing need to accurately understand the emotions and intentions of animals in communication between pets and their owners. However, there is a lack of technology to accurately analyze animal sounds and convey them in a way that is easily understood by humans. Furthermore, there is the challenge of conveying human messages in a way that animals can understand. In addition, there is a lack of systems in place at physical stores such as pet shops to support owners' purchasing decisions based on an understanding of the animals' condition.

[0714] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0715] In this invention, the server includes means for analyzing animal vocal information and identifying the animal's emotions or intentions; means for translating the identified emotions or intentions into natural language and transmitting them to an information terminal; and means for converting the natural language into a form that the animal can understand and outputting it to the animal. This facilitates smooth communication between animals and their owners, improves the customer experience in physical stores, and enables effective product recommendations.

[0716] "Animal vocal information" refers to digitized data of sounds emitted by animals. This data serves as a basis for analyzing animals' emotions and intentions.

[0717] A "central processing unit" refers to a computer system that receives, analyzes, and translates audio information. This device interacts with terminals via a network.

[0718] "Natural language" refers to the language that humans use on a daily basis, and is used to communicate the emotions and intentions of animals in a way that is easily understood by humans.

[0719] An "information terminal" refers to a device used by a user to receive and display information. Specifically, this includes smartphones and tablets.

[0720] "Animal products" refer to products tailored to the characteristics and needs of animals. Specifically, this includes toys, food, and care products, and the role is to support the recommendation of such products.

[0721] A "generative AI model" refers to an artificial intelligence framework that learns from data and performs tasks such as analyzing animal voices and generating natural language. It is used to support smooth communication between animals and humans.

[0722] To realize this invention, the server and terminal play a central role in the system. The server receives animal vocal information and analyzes it using a generative AI model. This analysis process uses an algorithm that identifies emotions and intentions from the animal's vocal characteristics. Specifically, it estimates the animal's state, such as "wanting to play" or "feeling anxious," based on the frequency components and rhythmic patterns of the vocals.

[0723] Once the analysis is complete, the server translates these estimation results into natural language. The translated results are then sent directly to the terminal. The terminal is the user's smartphone or tablet, which has the capability to display these translated results on its screen. The displayed information helps the user quickly understand their pet's condition and take appropriate action.

[0724] On the other hand, when a user enters a message into the device, the device sends that message back to the server. The server synthesizes the entered human language into speech that animals can understand. This synthesis technology typically includes the functions of a speech synthesis engine. The synthesized speech is played back from the device to the animal, enabling smooth communication.

[0725] As a concrete example, in pet shops, this system would be used to enable customers to understand their pet's feelings in real time and instantly purchase the necessary products. In this case, an example of a prompt text would be, "Analyze the dog's voice, estimate its emotions, and display the result in Japanese."

[0726] This system is expected to improve the quality of communication between pets and their owners, and further enhance customer service at pet shops.

[0727] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0728] Step 1:

[0729] The device records animal sounds using its microphone and saves them as digital audio data. The user launches the device's recording application and captures their pet's sounds using the record button. This recorded data is sent to the server as initial input data.

[0730] Step 2:

[0731] The server analyzes the received audio data. Using a generative AI model, it analyzes the frequency components and temporal features of the audio to estimate the animal's emotions and intentions. The estimation results are output as specific emotional states such as "want to play" or "anxious" through data calculations.

[0732] Step 3:

[0733] The server translates the analyzed emotions and intentions into natural language. Using a generative AI model, the estimated emotions are converted into standard Japanese, generating a message that is easy for the user to understand. This content is then formatted as data to be sent to the device.

[0734] Step 4:

[0735] The device receives the translation results sent from the server and displays them on the screen. Through the device screen, the user can understand their pet's emotional state. For example, a message such as "Your pet wants to play" might be displayed.

[0736] Step 5:

[0737] The user enters the message they want to convey to their pet using the input interface built into the device. This input is then sent back to the server as data and processed into a communication format for the animal.

[0738] Step 6:

[0739] The server converts user input messages into speech that animals can understand. Using a generative AI model, it synthesizes the input Japanese into animal-friendly speech with specific frequencies and intonations. This result is then constructed as output data.

[0740] Step 7:

[0741] The device plays the converted audio data received from the server and emits the voice to the animal. This conveys the user's intentions to the pet. This process is completed when the animal actually changes its behavior in response to the message.

[0742] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0743] This invention provides a system that combines an emotion engine that analyzes animal sounds and recognizes user emotions. This system aims to improve communication between animals and humans through the cooperation of a server and a terminal. Furthermore, by using the emotion engine, it achieves more appropriate interaction while considering the user's emotional state.

[0744] First, the device records the voices of both the user and the animal. During this process, the user's voice is analyzed by an emotion engine to identify the user's emotions, while the animal's voice is sent to the server.

[0745] After receiving animal voice data, the server uses an AI engine to analyze the data. This analysis identifies the animal's emotions and intentions, and then the process of translating this into human language begins.

[0746] Next, the emotion engine processes the user's emotional data and suggests the optimal communication content to convey to the animal. Specifically, if the user is feeling stressed, the content of the interaction with the animal can be adjusted to promote mutual relaxation.

[0747] Based on the translated animal's emotions or intentions, and suggestions from the emotion engine, the server sends information to the terminal. The terminal displays this information to the user. Based on this information, the user can decide how to respond to the animal.

[0748] Furthermore, when a user enters their own words, those words are sent back to the server and converted into an appropriate voice format for the animal. This ensures that the message is delivered to the animal and communication is completed.

[0749] As a concrete example, consider a scenario where a user is relaxing with their pet cat. If the cat makes a sound indicating it wants attention, the system will display the most appropriate interaction method based on the user's current emotional state.

[0750] This system allows users to interact with animals while harmonizing their own emotions with the animals' states, thereby improving their quality of life.

[0751] The following describes the processing flow.

[0752] Step 1:

[0753] The device simultaneously records audio data from both the user and the animal. Recording begins when the user presses the "Start Recording" button, and the device captures the data using its built-in microphone.

[0754] Step 2:

[0755] The device splits the recorded data into user voice data and animal voice data, saving them as temporary files. This operation is necessary to analyze the two voices individually.

[0756] Step 3:

[0757] The emotion engine analyzes the user's voice data to identify the user's emotional state. This process estimates emotions by evaluating factors such as tone, speed, and language patterns within the voice.

[0758] Step 4:

[0759] The device sends animal sound data to the server. A secure communication protocol is used for data transmission, and it is ensured that the data reaches the server accurately.

[0760] Step 5:

[0761] The server uses an AI engine to analyze the animal's voice data it receives. The server detects patterns in the animal's vocalizations and identifies the emotions and intentions they convey.

[0762] Step 6:

[0763] The server translates the analysis results into human language, expressing the animal's emotions and intentions. Simultaneously, it considers the user's emotional state to generate suggestions from the emotion engine.

[0764] Step 7:

[0765] The server sends the translation results and suggestions from the engine to the terminal. The terminal receives the information and promptly notifies the user.

[0766] Step 8:

[0767] The device displays the information it receives to the user. Based on the displayed information, the user can decide on appropriate actions and words for the animal.

[0768] Step 9:

[0769] The user enters a response into the terminal, and the terminal sends that input data to the server. This data is a message that should be understood by animals.

[0770] Step 10:

[0771] The server converts the user's words into an animal-readable voice format and sends this voice to the device. The device then plays this voice and communicates with the animal.

[0772] Thus, this system accurately recognizes the emotions of both the user and the animal, and highly optimizes communication.

[0773] (Example 2)

[0774] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0775] In animal-human communication, there is a need for a system that can accurately understand the animal's emotions and intentions, and enable appropriate human responses based on that understanding. However, conventional systems have the problem of low accuracy in identifying emotions from animal sounds and the inability to suggest communication that takes the user's emotions into consideration. Therefore, there is a need to provide a system that can realize ideal interaction between animals and humans and improve their quality of life.

[0776] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0777] In this invention, the server includes means for analyzing animal vocal information and identifying its emotions and intentions, means for converting the identified emotions and intentions into human language, and means for detecting the user's vocal emotions and suggesting a communication method that corresponds to the user's emotions. This enables a highly accurate understanding of the animal's emotions and intentions, as well as appropriate interaction that takes the user's emotions into consideration.

[0778] "Auditory information" refers to sound data obtained from animals or users, including elements such as pitch, intensity, and temporal changes in sound.

[0779] A "processing device" refers to a computer system that analyzes audio data to identify the emotions and intentions of animals.

[0780] "Emotion or intention" refers to the mental or behavioral state indicated by the sounds an animal makes, as determined by analysis.

[0781] "Human language" refers to the natural forms of language used to translate the intentions and emotions of animals, and which are understandable to humans.

[0782] A "terminal device" refers to a device that serves as an interface with the end user, allowing the user to receive and input voice information.

[0783] "Vocal emotion" refers to the emotional state emanating from the user's voice, including emotional responses such as stress and relaxation.

[0784] "Communication methods" refer to specific behaviors and ways of dialogue proposed to facilitate interaction with animals.

[0785] A "generative AI model" refers to an artificial intelligence model used for analyzing and translating speech data, and is the algorithm that underpins the entire process.

[0786] A "prompt statement" refers to a trigger statement that is input into the generation AI model. Based on this, the model operates and generates results.

[0787] This invention is a system for enhancing communication between animals and humans, where a server, terminal, and user work together seamlessly. The specific configuration for carrying out this invention is shown below.

[0788] First, the device acquires the voices of both the user and the animal. The device is a smartphone or a dedicated device that collects voice data in real time using its built-in microphone. The user's voice data is analyzed by an emotion engine within the device, and the user's emotions are identified, for example, as "peaceful" or "exhilarated." The animal's voice data is formatted and then sent to a server via the internet.

[0789] The server receives audio data and then analyzes it using an AI engine. Specifically, it uses generative AI models such as TensorFlow and PyTorch to identify emotions and intentions from animal voices. When it recognizes a state such as "excited" in the animal, it translates it into human language. This translated information is then sent to the terminal.

[0790] The user determines how to interact with the animal based on the information provided by the device. Furthermore, if the user has something they want to communicate to the animal, they can input it into the device. The input is then sent back to the server and converted into an animal-friendly voice format. For example, a message like "Let's play together" would be output in a voice customized for the animal.

[0791] As a concrete example, consider a scenario where a user is spending time with their pet dog. If the dog makes a sound indicating it wants to go outside, the system suggests an interaction method based on the user's current emotional state, such as "taking the dog for a walk with leadership." This system allows users to communicate in a way that harmonizes their own emotions while understanding the animal's state.

[0792] An example of a prompt message might be, "Analyze the sound of a dog barking and translate its emotion." This allows the system to function comprehensively and play a role in improving the quality of life for both animals and humans.

[0793] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0794] Step 1:

[0795] The device acquires user and animal voices in real time. When the user uses the device's microphone to collect voices, the audio data is immediately digitized and pre-processed to analyze the user's emotions. The input is the user's and animal's voices, and the output is digitized audio data. Specific operations include noise reduction and conversion of the audio to the time domain.

[0796] Step 2:

[0797] The device transmits the user's voice data to its built-in emotion engine. The emotion engine uses a generative AI model to analyze the characteristics of the voice and identify the user's emotional state, such as "relaxed" or "stressed." The input is the digitized user's voice, and the output is the identified emotional state. Specifically, the process involves spectrogram conversion and comparison with the emotion model.

[0798] Step 3:

[0799] The terminal transmits animal voice data to the server. For transmission, the voice data is effectively packaged and delivered to the server via a secure communication method. The input is digitized animal voice, and the output is the packaged data sent to the server. Specific operations include data compression and transfer using a secure protocol.

[0800] Step 4:

[0801] The server analyzes the received animal voice data using an AI engine. The generative AI model used here evaluates the animal's voice patterns and identifies its emotions and intentions. The input is the animal voice package received by the server, and the output is the identified emotions and intentions of the animal. Specifically, the process involves filtering the voice waveform and applying an emotion identification algorithm.

[0802] Step 5:

[0803] The server translates the identified animal's emotions or intentions into human language and sends it to the terminal. The translated information is provided in a format that is easy for the user to understand. The input is the identified animal's emotions or intentions, and the output is the translation into human language. Specifically, text generation is performed using a natural language processing module.

[0804] Step 6:

[0805] The user decides how to interact with the animal based on its state and emotions presented by the device. If necessary, the user interactively determines a course of action. The input is translated animal emotion information, and the output is the user's decision to act. The specific actions involve the user's decision-making process based on the provided information.

[0806] Step 7:

[0807] When a user wants to send a message to an animal, they type the words into the device. These words are sent to a server and converted into an animal-readable audio format. The input is text information entered by the user, and the output is played back on the device as audio for the animal. Specifically, text-to-speech technology is used for speech generation.

[0808] (Application Example 2)

[0809] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0810] Smooth communication between animals and humans is crucial for deepening mutual understanding, especially in relationships with pets. However, since animals cannot directly communicate with humans, accurately understanding their emotions and intentions is difficult. Furthermore, teaching animals appropriate communication methods based on human emotional states is an even more complex challenge. There is a need to solve these problems and develop safe and effective means of facilitating interaction between visitors and animals in pet shops and veterinary clinics.

[0811] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0812] In this invention, the server includes means for analyzing animal voice data to identify emotions or intentions, means for analyzing human emotion data to recommend optimal communication, and means for proposing interaction methods suitable for both animals and humans. This enables communication in which animals and humans can mutually understand each other's emotions and intentions.

[0813] "Animal sound data" refers to digital recordings of sounds emitted by animals.

[0814] A "server" is a computing device that receives and analyzes animal and human voice data.

[0815] "Means for identifying emotions or intentions" refers to technologies and algorithms for analyzing and revealing the emotions and behavioral intentions of animals from received audio data.

[0816] "Human emotion data" refers to data used to identify a person's emotional state based on their voice and other biometric information.

[0817] "Means of recommending optimal communication" refers to technologies and systems that propose methods for smooth interaction between humans and animals based on analyzed emotional data.

[0818] A "terminal" is a device that displays information sent from a server to the user and also accepts input from the user.

[0819] "Translation means" are technologies or devices that translate animal emotions or intentions into language that humans can understand, or vice versa.

[0820] "Means of proposing methods of interaction" refer to technologies and functions that present optimal methods of interaction while taking into account the emotions of animals and humans.

[0821] The system for implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user.

[0822] First, the device is equipped with microphones to record animal and user voices. The recorded audio data is sent to a server in digital format. The server uses an advanced analysis engine to identify the emotions and intentions of the animal's voice. The software used includes natural language processing libraries and speech sentiment analysis libraries (e.g., Python's NLTK and OpenAI models).

[0823] Next, the server uses an emotion recognition engine (e.g., Microsoft Azure Emotion API) to analyze the user's voice and recognize their emotions. This emotion data is then analyzed in conjunction with animal emotion data and used in a process to suggest the most appropriate communication method. The recommendations generated by the AI ​​model are presented to the user visually through the device's display.

[0824] Users can view suggested methods via their device and respond to animals using their own actions and voice. The voice input and choices from the user are sent back to the server and converted into speech that animals can understand. This conversion uses text-to-speech technology (e.g., Google Text-to-Speech).

[0825] As a concrete example, let's consider an application in a pet shop. When a customer is interacting with a cat in the store, if the cat makes a sound indicating it wants to play, the system will use the user's emotional state to suggest the best way for the user to interact with the cat. For example, a user who is feeling stressed will be offered suggestions for conversation and play to help them relax with the cat. Examples of prompts in this case could include, "We will analyze the sounds the cat made to understand its emotions," or "We will suggest how the user should interact to help them relax."

[0826] This system offers an innovative means for better communication between animals and humans, and its implementation is particularly useful in places where contact with animals is frequent.

[0827] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0828] Step 1:

[0829] The device simultaneously records the voices of both the user and the animal. The input is real-time audio data obtained through the device's microphone. This audio data is converted to a digital format and prepared for transmission to the server.

[0830] Step 2:

[0831] The server receives animal voice data sent from the terminal. The server uses an AI engine to analyze this input data, interpreting the animal's emotions and intentions. Here, a natural language processing library is used to process the data and convert it into human language for translation.

[0832] Step 3:

[0833] The server receives the user's voice data and uses an emotion engine to analyze the user's emotional state. The input voice data is converted into text data through the engine, and the user's emotions are output as numerical and textual information. This output is used for subsequent analysis.

[0834] Step 4:

[0835] The server determines the optimal communication method based on the analyzed animal's emotions and the user's emotions. A generative AI model is used here to create specific dialogue content as prompts. The output is information about the proposed interaction content.

[0836] Step 5:

[0837] The terminal receives information about the interaction content sent from the server and visualizes it for the user. Specific action instructions and communication methods displayed on the terminal are output in a format that the user can easily understand.

[0838] Step 6:

[0839] The user communicates with the animal according to the information presented through the device. The user's input (e.g., selected communication mode) is resent from the device to the server and proceeds to the step where it is converted into voice for the animal.

[0840] Step 7:

[0841] The server converts the user's input into an audio format that animals can understand and outputs it to the animals via the terminal. Here, the text-to-speech conversion process takes place, resulting in output data for directly approaching the animals.

[0842] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0843] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0844] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0845] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0846] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0847] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0848] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0849] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0850] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0851] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0852] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0853] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0854] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0855] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0856] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0857] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0858] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0859] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0860] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0861] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0862] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0863] The following is further disclosed regarding the embodiments described above.

[0864] (Claim 1)

[0865] A means of acquiring animal sound data,

[0866] Means for transmitting the aforementioned audio data to a server,

[0867] The server analyzes the aforementioned audio data and provides means for identifying the animal's emotions or intentions,

[0868] A means of translating a specified emotion or intention into human language and transmitting it to a terminal,

[0869] A means for converting human speech into sounds that animals can understand and outputting them to the animal,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] A means of inputting human language,

[0873] A means of sending the input words to the server,

[0874] A means for translating the aforementioned words into animal sounds,

[0875] A means of outputting translated animal sounds,

[0876] The system according to claim 1, including the following:

[0877] (Claim 3)

[0878] The aforementioned server processes the audio data using a natural language processing module and provides means for translating it into human language.

[0879] A means equipped with an algorithm for analyzing vocal characteristics according to animal species,

[0880] The system according to claim 1, including the following:

[0881] "Example 1"

[0882] (Claim 1)

[0883] A means of acquiring animal vocal information,

[0884] means for transmitting the aforementioned audio information to an information processing device,

[0885] An information processing device includes means for analyzing the aforementioned audio information and identifying the emotions or intentions of a living being,

[0886] Means for translating identified emotions or intentions into language and transmitting them to a terminal device,

[0887] A means for converting language into sounds that a living organism can understand and outputting them to the organism,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] Means of inputting language,

[0891] Means for transmitting the input language to an information processing device,

[0892] A means for translating the aforementioned language into biological sounds,

[0893] A means of outputting translated biological sounds,

[0894] The system according to claim 1, including the following:

[0895] (Claim 3)

[0896] The aforementioned information processing device includes means for processing audio information with a natural language processing function and translating it into language,

[0897] A means comprising a procedure for analyzing vocal characteristics according to the species of organism,

[0898] The system according to claim 1, including the following:

[0899] "Application Example 1"

[0900] (Claim 1)

[0901] Technical means for acquiring animal vocal information,

[0902] Technical means for transmitting acquired audio information to a central processing unit,

[0903] A technical means for analyzing voice information in a central processing unit to identify the emotions or intentions of an animal,

[0904] A technical means for translating identified emotions or intentions into natural language and transmitting them to an information terminal,

[0905] A technological means to convert natural language into a form that animals can understand and output it to animals,

[0906] Technological means to support interaction between humans and animals via information terminals within a store,

[0907] A system that includes this.

[0908] (Claim 2)

[0909] A technological means for inputting human language information,

[0910] Technical means for transmitting input language information to a central processing unit,

[0911] A technical means for translating the aforementioned linguistic information into animal information,

[0912] A technical means for outputting translated animal information,

[0913] The system according to claim 1, comprising technical means for assisting in the selection of animal products.

[0914] (Claim 3)

[0915] A technical means by which a central processing unit processes speech information using a natural language processing module and translates it into natural language,

[0916] A technical means equipped with an algorithm for analyzing vocal characteristics according to the type of animal,

[0917] The system according to claim 1, comprising technical means for providing an interactive interaction experience using a generative AI model.

[0918] "Example 2 of combining an emotion engine"

[0919] (Claim 1)

[0920] A means of acquiring animal vocal information,

[0921] means for transmitting the aforementioned audio information to a processing device,

[0922] The processing device includes means for analyzing the audio information and identifying the animal's emotions or intentions,

[0923] Means for translating identified emotions or intentions into human language and transmitting them to a terminal device,

[0924] A means for converting human language into sounds that can be recognized by animals and providing them to the animals,

[0925] A means to detect the user's voice emotions and propose effective communication methods with animals that correspond to the user's emotions,

[0926] A system that includes this.

[0927] (Claim 2)

[0928] A means of inputting the user's language,

[0929] Means for transmitting the input language to a processing unit,

[0930] A means for translating the aforementioned language into animal sounds,

[0931] A means of providing translated animal sounds,

[0932] The system according to claim 1, including the following:

[0933] (Claim 3)

[0934] The aforementioned processing device includes means for processing speech information with a natural language processing module and converting it into human language,

[0935] A means comprising a method for analyzing vocal characteristics according to animal species,

[0936] A means for optimizing interaction with animals using prompt sentences based on a generative AI model,

[0937] The system according to claim 1, including the following:

[0938] "Application example 2 when combining with an emotional engine"

[0939] (Claim 1)

[0940] A means of acquiring animal sound data,

[0941] Means for transmitting the aforementioned audio data to a server,

[0942] The server analyzes the aforementioned audio data and provides means for identifying the animal's emotions or intentions,

[0943] A means of translating a specified emotion or intention into human language and transmitting it to a terminal,

[0944] A means of acquiring and analyzing human emotional data to recommend the optimal dialogue content for communication with animals,

[0945] A means for converting human speech into sounds that animals can understand and outputting them to the animal,

[0946] A means by which the device presents the user with ways to interact with animals,

[0947] A system that includes this.

[0948] (Claim 2)

[0949] A means of inputting human language,

[0950] A means of sending the input words to the server,

[0951] A means for translating the aforementioned words into animal sounds,

[0952] A means of outputting translated animal sounds,

[0953] A means by which the terminal adjusts and presents dialogue content in accordance with human emotions,

[0954] The system according to claim 1, including the following:

[0955] (Claim 3)

[0956] The aforementioned server processes the audio data using a natural language processing module and provides means for translating it into human language.

[0957] A means equipped with an algorithm for analyzing vocal characteristics according to animal species,

[0958] A means to optimize the way we interact with animals by utilizing an emotion engine that analyzes user emotions,

[0959] The system according to claim 1, including the following: [Explanation of symbols]

[0960] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring animal sound data, Means for transmitting the aforementioned audio data to a server, The server analyzes the aforementioned audio data and provides means for identifying the animal's emotions or intentions, A means of translating a specified emotion or intention into human language and transmitting it to a terminal, A means for converting human speech into sounds that animals can understand and outputting them to the animal, A system that includes this.

2. A means of inputting human language, A means of sending the input words to the server, A means for translating the aforementioned words into animal sounds, A means of outputting translated animal sounds, The system according to claim 1, including the following:

3. The aforementioned server processes the audio data using a natural language processing module and provides means for translating it into human language. A means equipped with an algorithm for analyzing vocal characteristics according to animal species, The system according to claim 1, including the following:

Images